Elevator system and equipment planning device

Abstract

The purpose of the present disclosure is to provide smooth guidance for boarding an elevator by a robot even in a crowded situation. An elevator system (101) according to the present disclosure comprises: a robot (12) which autonomously moves in a building in which an elevator (14) having a plurality of cars is installed and measures human flow data around the robot using a measuring device mounted on the robot; and a human flow control unit (11) which causes the robot (12) to perform human flow control for controlling human flow moving toward the elevator (14) on the basis of the human flow data measured by the robot (12) and elevator operation data. The human flow control involves displaying paths to the cars of the elevator (14) by projection mapping on the floor of an elevator hall (15) so that the paths do not overlap each other.

Description

Technical Field

[0001] This disclosure relates to an elevator system and a facility planning device.

Background Art

[0002] Patent Document 1 describes an elevator system including an elevator control device, a robot control device, and an integrated management device that integrally manages the elevator control device and the robot control device. The elevator system of Patent Document 1 aims to improve the transportation capacity by achieving both improved elevator riding efficiency and smooth boarding.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the elevator system of Patent Document 1, a robot moves to the position of an elevator passenger to provide boarding guidance. Therefore, in a congested situation where a large number of passengers are staying in the elevator hall, there is no space for the robot to move, and there is a problem that boarding guidance by the robot cannot be performed.

[0005] This disclosure has been made to solve the above problems, and an object thereof is to smoothly perform boarding guidance to an elevator by a robot even in a congested situation.

Means for Solving the Problems

[0006] In this disclosure A certain typeThe elevator system comprises a robot that autonomously moves within a building equipped with multiple elevator cars and measures pedestrian flow data around itself using a measuring device mounted on it, and a pedestrian flow control unit that controls the flow of people towards the elevator based on the pedestrian flow data measured by the robot and the elevator operation data. The pedestrian flow control unit determines a designated location where the robot should next measure pedestrian flow data, based on the pedestrian flow data measured by the robot, and the robot measures the pedestrian flow data at the designated location. ru. [Effects of the Invention]

[0007] According to the elevator system of this disclosure, pedestrian flow control is performed, making it possible to smoothly guide robots to board elevators even in crowded conditions. The purpose, features, embodiments, and advantages of this disclosure will become clearer from the following detailed description and accompanying drawings. [Brief explanation of the drawing]

[0008] [Figure 1] This is a diagram showing the configuration of an elevator system according to Embodiment 1. [Figure 2] This diagram shows the flow of people in an elevator hall. [Figure 3] This diagram shows the flow of people in an elevator hall with robot-controlled pedestrian flow. [Figure 4] This diagram shows network data representing the route to the elevator. [Figure 5] This diagram shows network data representing the route to the elevator. [Figure 6] This diagram shows network data representing the route to the elevator. [Figure 7] This is a flowchart showing the operation of the pedestrian flow control unit according to Embodiment 1. [Figure 8] This is a flowchart showing the operation of the control unit according to Embodiment 1. [Figure 9] This figure shows a time-series network used for evaluating congestion levels. [Figure 10]It is a diagram showing a state in which a crowd control that restricts movement to congested nodes is performed by a robot. [Figure 11] It is a diagram showing the congestion level of each node after crowd control. [Figure 12] It is a flowchart showing the operation of the crowd control unit according to Embodiment 2. [Figure 13] It is a configuration diagram of an elevator system according to Embodiment 3. [Figure 14] It is a flowchart showing the operation of the crowd control unit according to Embodiment 3. [Figure 15] It is a flowchart showing the operation of the operation control unit according to Embodiment 3. [Figure 16] It is a configuration diagram of an elevator system according to Embodiment 4. [Figure 17] It is a flowchart showing the operation of the crowd control unit according to Embodiment 4. [Figure 18] It is a flowchart showing the operation of the operation control unit according to Embodiment 4. [Figure 19] It is a flowchart showing the operation of the learning unit according to Embodiment 4. [Figure 20] It is a configuration diagram of an equipment planning device according to Embodiment 5. [Figure 21] It is a flowchart showing the operation of the equipment design unit according to Embodiment 5. [Figure 22] It is a diagram showing the hardware configuration of an elevator system and an equipment planning device. [Figure 23] It is a diagram showing the hardware configuration of an elevator system and an equipment planning device.

Embodiments for Carrying Out the Invention

[0009] <A. Embodiment 1> <A-1. Configuration> FIG. 1 is a configuration diagram of an elevator system 101 according to Embodiment 1. The elevator system 101 includes a crowd control unit 11, a robot 12, an operation control unit 13, and an elevator 14.

[0010] The crowd flow control unit 11 controls the crowd flow towards the elevator 14 by controlling the robot 12. Specifically, the crowd flow control unit 11 determines the control content of the robot 12 and transmits control information including the determined control content to the robot 12.

[0011] Based on the control information obtained from the crowd flow control unit 11, the robot 12 moves autonomously to control the crowd flow and acquire crowd flow data. The crowd flow data is data that can grasp when, where, and how many people are present. As a configuration for the robot 12 to acquire the crowd flow data, for example, it is equipped with a camera or a sensor. When the robot 12 acquires the crowd flow data, it transmits the crowd flow data together with the position information of the robot 12 at the time when the crowd flow data is acquired to the crowd flow control unit 11. Also, as a configuration for the robot 12 to perform crowd flow control, it is equipped with a projection device that projects an image onto the floor or wall. As another configuration for the robot 12 to perform crowd flow control, it may be equipped with a touch panel, a display, or a speaker.

[0012] The operation control unit 13 controls the operation of the elevator 14 installed in a building such as a building. The operation control unit 13 and the elevator 14 communicate information. The operation control unit 13 receives the operation data of the elevator 14 from the elevator 14. The operation data includes the operation information of the elevator car, for example, information such as the position, speed, door opening / closing state, or load of the car. The operation control unit 13 determines the operation control content of the elevator 14 based on the operation data and transmits operation control information including the determined operation control content to the elevator 14.

[0013] The elevator 14 operates based on the operation control information received from the operation control unit 13.

[0014] <A-2. Operation> Referring to Figures 2 and 3, the operation of the elevator system 101 will be explained. Figure 2 shows the flow of people in the elevator hall when the elevator system 101 is not controlling the flow of people. The elevator 14 has three cars, which are referred to as elevator A 14A, elevator B 14B, and elevator C 14C. Passengers who proceed from the corridor 16 to the elevator hall 15 board one of the elevator cars A 14A, B 14B, or C 14C from the elevator hall 15.

[0015] As shown in Figure 2, if passenger flow control is not implemented, multiple passengers will board the desired elevator in a disorderly manner, causing their paths to intersect and creating a risk of collisions.

[0016] Figure 3 shows the flow of people in the elevator hall when the elevator system 101 controls the flow of people. Robots 12A, 12B, and 12C are installed in the elevator hall 15 or passageway 16. Robot 12A displays the route 17A to elevator A 14A in the elevator hall 15 on the floor of the elevator hall 15 using projection mapping. Similarly, robots 12B and 12C display the routes 17A and 17B to elevators B 14B and C 14C in the elevator hall 15 on the floor of the elevator hall 15 using projection mapping. Here, routes 17A, 17B, and 17C are set so that they do not intersect or overlap with each other.

[0017] Passengers proceed along one of the routes 17A, 17B, or 17C marked on the floor of the elevator hall 15 to the elevator car they intend to board. This prevents the routes of passengers heading to different elevator cars from intersecting in the elevator hall 15, thus avoiding collisions between passengers. As a result, each passenger can board the elevator 14 smoothly, improving the transport efficiency of the elevator 14.

[0018] The passenger flow control unit 11 and the operation control unit 13 handle network data. Network data represents each location in the building where the elevator 14 is installed as a node, and connects the nodes to which people can move with edges. Figures 4 to 6 show the permissible network data, which is the network data created by the passenger flow control unit 11.

[0019] In the example shown in Figure 4, the passageway 16, elevator hall 15, and elevator 14 shown in Figure 3 are represented as nodes 51, 52, and 53, respectively. Furthermore, an edge 61 is connected to node 51, an edge 62 is connected between nodes 51 and 52, and an edge 63 is connected between nodes 52 and 53.

[0020] As shown in Figure 5, nodes 51, 52, and 53 have values ​​that represent the capacity of the corresponding location. The values ​​for nodes 51, 52, and 53 are V1, V2, and V3, respectively.

[0021] As shown in Figure 6, each edge 61, 62, and 63 has a value representing the number of people that can be moved per unit time. The values ​​for edges 61, 62, and 63 are e1, e2, and e3, respectively.

[0022] Furthermore, the passenger flow control unit 11 and the operation control unit 13 may also handle actual network data in addition to the permissible network data. The actual network data is obtained by changing the node values ​​in the permissible network data to a time series of the number of people actually present at the corresponding location, and changing the edge values ​​to a time series of the number of people actually moving between nodes per unit time.

[0023] Figure 7 is a flowchart illustrating the operation of the pedestrian flow control unit 11. The operation of the pedestrian flow control unit 11 will be explained below in accordance with the flow shown in Figure 7. First, in step S101, the pedestrian flow control unit 11 receives pedestrian flow data and position information from the robot 12. The pedestrian flow data received here is acquired by the robot 12 using a camera or sensors. The position information is the coordinates at the time the robot 12 acquired the pedestrian flow data.

[0024] Next, in step S102, the passenger flow control unit 11 obtains the number of passengers boarding and alighting the elevator 14 on each floor (hereinafter referred to as "number of passengers boarding and alighting") from the operation control unit 13.

[0025] Subsequently, in step S103, the pedestrian flow control unit 11 creates actual network data based on the data acquired in steps S101 and S102. From the pedestrian flow data received in step S101, the pedestrian flow control unit 11 obtains the number of people present at the node where the robot 12 is located, and the number of people moving between the node where the robot 12 is located and adjacent nodes. In addition, from the number of people getting on and off the elevator acquired in step S102, the pedestrian flow control unit 11 obtains the number of people moving between node 52 of the elevator hall 15 and node 53 of the elevator 14 on each floor.

[0026] Next, in step S104, the passenger flow control unit 11 transmits the actual network data created in step S103 to the operation control unit 13.

[0027] Subsequently, in step S105, the pedestrian flow control unit 11 determines whether or not it has received a request for pedestrian flow control from the operation control unit 13. If there is no request for pedestrian flow control, the pedestrian flow control unit 11 terminates its processing.

[0028] If a request for passenger flow control is received, in step S106, the passenger flow control unit 11 sets the content of the passenger flow control according to the request. The request may relate to guidance from the landing call registration device installed in the elevator hall 15 to the passenger elevator. The content of the control may be voice guidance or projection mapping. For example, projection mapping may be used to project computer graphics (CG) of the route connecting the landing call registration device and each passenger elevator. Alternatively, voice guidance may be used to instruct passengers to move along the CG route projected on the floor. The request may also relate to acquiring passenger flow in front of the elevator doors or near the landing call registration device.

[0029] After step S106, in step S107, the pedestrian flow control unit 11 transmits control data, including the pedestrian flow control settings configured in step S106, to the robot 12. This completes the processing of the pedestrian flow control unit 11.

[0030] Figure 8 is a flowchart showing the operation of the operation control unit 13 according to Embodiment 1. The operation of the operation control unit 13 will be described below in accordance with the flow shown in Figure 8.

[0031] First, in step S201, the operation control unit 13 acquires operation data from the elevator 14. The operation data includes the operation log of the elevator 14, such as the car load over time, running status, door opening / closing status, and car position.

[0032] Next, in step S202, the operation control unit 13 calculates the number of passengers getting on and off the elevator 14 on each floor based on the operation data. The operation control unit 13 determines the floor where the elevator car is located from its position and calculates the number of passengers getting on and off by dividing the change in car load when the elevator is stopped and the doors are open by the load per passenger. If the car load increases, it relates to passengers getting on; if the car load decreases, it relates to passengers getting off.

[0033] Subsequently, in step S203, the operation control unit 13 transmits the number of passengers getting on and off at each floor, calculated in step S202, to the passenger flow control unit 11.

[0034] Next, in step S204, the operation control unit 13 acquires actual network data from the passenger flow control unit 11. This actual network data contains the number of people present in the elevator hall 15 and the number of people moving from the elevator hall 15 to the elevator 14.

[0035] After that, in step S205, the operation control unit 13 obtains the number of people to be transported required for the elevator 14 on each floor from the actual network data. Specifically, the operation control unit 13 uses the number of people present in the elevator hall 15 in the actual network data as the number of people to be transported required for the elevator 14. Alternatively, the operation control unit 13 may use the number of people moving from the passage 16 to the elevator hall 15 in the actual network data as the number of people to be transported required for the elevator 14.

[0036] Next, in step S206, the operation control unit 13 determines whether people flow control is necessary. The operation control unit 13 calculates the transportable number of people, which is the number of people that the elevator 14 can transport, based on the operation data. Then, when the number of people present in the elevator hall 15 is greater than the transportable number of people, but the number of people moving from the elevator hall 15 to the elevator 14 is less than the transportable number of people, it is determined that people flow control is necessary. Alternatively, the operation control unit 13 may determine that the elevator hall 15 is congested and that people flow control is necessary when the number of people present in the elevator hall 15 is greater than a predetermined number of people.

[0037] When people flow control is not necessary, the operation control unit 13 ends the process. On the other hand, when people flow control is necessary, in step S207, the operation control unit 13 sends a request for people flow control to the people flow control unit 11. Thus, the process of the operation control unit 13 ends.

[0038] <A-3. Effect> As described above, the elevator system 101 according to Embodiment 1 includes a robot 12 that autonomously moves within a building in which an elevator 14 having a plurality of carriages is installed, and measures the people flow data around itself with a measuring device mounted on itself, and a people flow control unit 11 that causes the robot 12 to perform people flow control, which is the control of the people flow toward the elevator 14, based on the people flow data measured by the robot 12 and the operation data of the elevator 14. Therefore, even under congested conditions, the robot 12 can guide the users safely and smoothly to the carriage in which they can board. As a result, a decrease in the transport efficiency of the elevator 14 is suppressed.

[0039] <B. Embodiment 2> <B-1. Configuration> The configuration of the elevator system 102 according to Embodiment 2 is as shown in FIG. 1 and is the same as the configuration of the elevator system 101 according to Embodiment 1.

[0040] <B-2. Operation> In the elevator system 101 according to Embodiment 1, the robot 12 performs the flow control of people to exert the transportation capacity of the elevator 14, thereby alleviating the congestion in the elevator hall 15.

[0041] However, when there are passengers exceeding the transportation capacity of the elevator 14 in the elevator hall 15 and more passengers flow into the elevator hall 15, the elevator hall 15 becomes congested. When it becomes congested, the moving space and the field of vision of the passengers are narrowed, so it is difficult for the flow control of people to exert its effect, and there are also risks such as collisions due to congestion.

[0042] Therefore, in the elevator system 102 of the present embodiment, in a congested situation where there are passengers exceeding the transportation capacity of the elevator 14 in the elevator hall 15, the movement of the passengers into the elevator hall 15 is suppressed. At this time, the robot 12 moves near the entrance of the elevator hall 15 and prompts by voice guidance or physically blocks the entrance so as not to move into the elevator hall 15.

[0043] The flow control unit 11 creates evaluation network data, which is network data for evaluating the congestion level of the nodes, from the allowable network data and the actual network data described in Embodiment 1.

[0044] Figure 9 shows the evaluation network data. In the evaluation network data, each node 51, 52, and 53 has a value representing the degree of congestion. The degree of congestion is calculated by dividing the number of people present at each node in the actual network data by the allowable number of people at each node in the allowable network data. In Figure 9, node 51 in corridor 16 has a congestion level of 30%, node 52 in elevator hall 15 has a congestion level of 90%, and node 53 in elevator 14 has a congestion level of 60%.

[0045] The pedestrian flow control unit 11 classifies nodes whose congestion level is above a predetermined first threshold into congested nodes, and all other nodes into non-congested nodes. If a congestion level of 80% is set as the threshold for a congested node, node 52 in the elevator hall 15 is classified as a congested node, and the other nodes 51 and 53 are classified as non-congested nodes.

[0046] The pedestrian flow control unit 11 places a robot 12 between the passageway 16 and the elevator hall 15 in order to limit the amount of people flowing into node 52 of the elevator hall 15, which is a congested node. This state is shown in Figure 10.

[0047] Figure 11 shows the congestion level of each node after pedestrian flow control by robot 12. As shown in Figure 11, the congestion level of passageway 16 increased from 30% to 45%, while the congestion level of elevator hall 15 decreased from 90% to 60%, thus easing congestion in elevator hall 15. Although the congestion level of passageway 16 is 45%, it is not high enough to be classified as a congested node.

[0048] Figure 12 is a flowchart illustrating the operation of the passenger flow control unit 11 in the elevator system 102. The operation of the passenger flow control unit 11 in the elevator system 102 will be explained below in accordance with Figure 12.

[0049] First, in step S301, the pedestrian flow control unit 11 receives pedestrian flow data and position information from the robot 12. This step is the same as step S101 in Figure 7.

[0050] Next, in step S302, the passenger flow control unit 11 obtains the number of passengers getting on and off the elevator 14 on each floor from the operation control unit 13. This step is the same as step S102 in Figure 7.

[0051] Subsequently, in step S303, the pedestrian flow control unit 11 creates actual network data based on the data acquired in steps S301 and S302. This step is the same as step S103 in Figure 7.

[0052] Next, in step S304, the pedestrian flow control unit 11 creates evaluation network data based on the actual network data and the acceptable network data.

[0053] Subsequently, in step S305, the pedestrian flow control unit 11 determines whether or not there are congested nodes in the evaluation network data. As explained in Figure 9, a node with a congestion level equal to or greater than a predetermined value is considered a congested node. The congestion threshold for determining a congested node is derived, for example, based on the area of ​​the elevator hall 15 and the personal space required to maintain safety or comfort. If there are no congested nodes, the processing of the pedestrian flow control unit 11 ends.

[0054] If there is a congested node, in step S306, the pedestrian flow control unit 11 determines whether the adjacent node to which the inflow edge to the congested node is connected is an empty node. Whether a node is empty or not is determined, for example, according to the following calculation. For the node to be determined as an empty node or not (hereinafter referred to as the node to be determined), let the allowable number of people be V and the number of people present be v. Then, let e_in be the number of passengers flowing into the node to be determined per unit time, and let e_out be the number of passengers flowing out from the node to the congested node per unit time. Let e_out' be the number of passengers flowing out to the congested node per unit time that is expected to decrease due to pedestrian flow control.

[0055] Assuming that the duration of the passenger flow control is T, the number of people present in the node to be determined increases by (e_in - e_out´)×T. If the difference (V - v) between the allowable number of people and the number of people present in the node to be determined is greater than or equal to the increase in the number of people present due to the passenger flow control (e_in - e_out´)×T, the node to be determined is determined to be an empty node.

[0056] The passenger flow control unit 11 may group a plurality of adjacent nodes into one and determine whether these plurality of nodes are empty nodes. In this case, the determination is made using the total allowable number of people, the number of people present, the number of incoming passengers when the plurality of nodes are regarded as one node, and the number of outgoing passengers to the congested node for the plurality of nodes.

[0057] If the adjacent node is not an empty node in step S306, the process of the passenger flow control unit 11 ends. On the other hand, if the adjacent node is an empty node in step S306, in step S307, the passenger flow control unit 11 sets a passenger flow control to suppress the inflow from the empty node to the congested node. For example, when the elevator hall 15 is a congested node and the passage 16 is an empty node, the passenger flow control unit 11 moves the robot 12 to the vicinity of the entrance from the passage 16 to the elevator hall 15, prompts it not to move to the elevator hall 15 by voice guidance, or physically blocks the entrance to the elevator hall 15, etc., and determines these as the control contents for the robot 12.

[0058] After step S307, in step S308, the passenger flow control unit 11 transmits control data including the control contents set in step S307 to the robot 12.

[0059] <B-3. Effect> In the elevator system 102 according to Embodiment 2, the passenger flow control unit 11 determines nodes with a congestion level equal to or higher than a predetermined threshold value as congested nodes. And the passenger flow control includes restricting the inflow of people into the congested nodes. Thereby, for example, when there are passengers in the elevator hall 15 who exceed the transportation capacity of the elevator 14, the congestion in the elevator hall 15 can be dispersed to the previous passage 16 and alleviated. Also, by alleviating the congestion in the elevator hall 15, the route guidance of passengers to the boarding signal device of the elevator 14 can be effectively performed, and the deterioration of the transportation efficiency of the elevator 14 can be prevented.

[0060] <C. Embodiment 3> <C-1. Configuration> FIG. 13 is a configuration diagram of an elevator system 103 according to Embodiment 3. The elevator system 103 includes a landing call registration device 18 in addition to the configuration of the elevator system 101 according to Embodiment 1.

[0061] The passenger flow control unit 11 causes the robot 12 to move to a designated position and acquire passenger flow data. For example, by acquiring the passenger flow data on the path connecting to the elevator hall 15, it is possible to predict the congestion in the elevator hall 15. Also, if the number of landing call registration devices 18 is variable, the number of landing call registration devices 18 that can meet the demand can be set by acquiring the passenger flow data in front of the landing call registration device 18.

[0062] The robot 12 moves and acquires passenger flow data according to the control of the passenger flow control unit 11. The passenger flow control unit 11 generates control data for the robot 12 according to the previous passenger flow data and the data acquired from the operation control unit 13.

[0063] The operation control unit 13 manages the landing call registration device 18 in addition to the elevator 14. Under the control of the operation control unit 13, the number of installed landing call registration devices 18 is variable. The number of installed landing call registration devices 18 is changed by the self-propelled movement of the landing call registration device 18 or by moving the landing call registration device 18 manually by a person. Alternatively, when the landing call registration device 18 is composed of digital signage such as an advertising panel, the number of installed landing call registration devices 18 may be changed by switching the display content of the digital signage.

[0064] The landing call registration device 18 communicates with the elevator 14. When a passenger operates the landing call registration device 18, the landing call registration device 18 transmits call registration data to the elevator 14, and a call is registered in the elevator 14. The elevator 14 determines a boarding machine number for the call and transmits the boarding machine number data to the landing call registration device 18. The landing call registration device 18 guides the passenger to the boarding machine number. In addition, the landing call registration device 18 transmits an operation log to the elevator 14, and the elevator 14 has the operation log of the landing call registration device 18.

[0065] <C-2. Operation> FIG. 14 is a flowchart showing the operation of the crowd control unit 11 in the third embodiment. Hereinafter, the operation of the crowd control unit 11 will be described along the flow of FIG. 14.

[0066] First, in step S401, the crowd control unit 11 acquires crowd data and position information from the robot 12. The crowd data and position information received here are not related to the position specified by the crowd control unit 11.

[0067] Next, in step S402, the crowd control unit 11 acquires operation data from the operation control unit 13. This operation data includes the position of the landing call registration device 18 and the log data of the landing call registration device 18 in addition to the operation log of the elevator 14.

[0068] Subsequently, in step S403, the pedestrian flow control unit 11 determines, based on the operation data, whether or not there is a designated location where pedestrian flow data should be acquired. For example, if the pedestrian flow control unit 11 determines, based on previous actual network data and operation control, that the elevator hall 15 is currently empty, it will decide to move the robot 12 to a designated location, such as the passage 16 leading to the elevator hall 15, in order to prepare for future congestion, and to acquire pedestrian flow data in the passage 16. In other words, the pedestrian flow control unit 11 determines that the passage 16 is the designated location.

[0069] Alternatively, if the passenger flow control unit 11 is frequently used, it determines that congestion is occurring in front of the boarding call registration device 18 and identifies the boarding call registration device 18 as a designated location. For example, based on the operation data acquired from the operation control unit 13, the passenger flow control unit 11 determines that congestion is occurring in front of the boarding call registration device 18 if the interval between uses of the boarding call registration device 18 is below a predetermined threshold for a certain period of time or longer.

[0070] If no designated position exists in step S403, the pedestrian flow control unit 11 proceeds to step S411.

[0071] If a designated location exists in step S403, the pedestrian flow control unit 11 sets the acquisition of pedestrian flow data at the designated location as the control content in step S404.

[0072] After step S404, in step S405, the pedestrian flow control unit 11 transmits control data, including the control content set in step S404, to the robot 12.

[0073] After step S405, in step S406, the pedestrian flow control unit 11 receives pedestrian flow data and position information at a specified location from the robot 12.

[0074] Steps S407 to S412, following step S406, are the same as steps S102 to S106 in Figure 7, so their explanation is omitted.

[0075] Figure 15 is a flowchart showing the operation of the operation control unit 13 in Embodiment 3. Hereinafter, the operation of the operation control unit 13 will be described along the flowchart of Figure 15.

[0076] First, in step S501, the operation control unit 13 acquires operation data from the elevator 14. This operation data includes, in addition to the operation log of the elevator 14, the position of the landing call registration device 18 and the log of the landing call registration device 18.

[0077] Next, in step S502, the operation control unit 13 transmits the operation data to the crowd control unit 11. Since steps S503 to S505 after that are the same as steps S202 to S204 in Figure 8, the description thereof will be omitted.

[0078] After step S505, in step S506, the operation control unit 13 sets the content of operation control based on the actual network data acquired in step S505. For example, if the number of people flowing into the node connected to the elevator hall 15 is large, the operation control unit 13 determines that the elevator hall 15 will be congested in the future, and sets operation control to improve the transportation efficiency from the elevator hall 15 in advance.

[0079] Alternatively, if the node of the landing call registration device 18 is congested, the operation control unit 13 increases the number of landing call registration devices 18 so that the waiting time from when lining up in the column of the landing call registration device 18 until operation is within a predetermined time.

[0080] Thereafter, in step S507, the operation control unit 13 transmits operation control data including the content of operation control set in step S506 to the elevator 14 and the landing call registration device 18.

[0081] <C-3. Effect> In the elevator system 103 according to Embodiment 3, the crowd control unit 11 determines a designated position where the robot 12 should next measure crowd data based on the crowd data measured by the robot 12. Then, the robot 12 measures the crowd data at the designated position. Thereby, the crowd control unit 11 can accurately grasp the crowd flow in the building and perform crowd control.

[0082] <D. Embodiment 4> <D-1. Configuration> FIG. 16 is a configuration diagram of an elevator system 104 according to Embodiment 4. The elevator system 104 is obtained by adding a learning unit 19 to the elevator system 103 according to Embodiment 3. Alternatively, the elevator system 104 may be obtained by adding a learning unit 19 to the elevator system 101 according to Embodiment 1.

[0083] The learning unit 19 exchanges data with the crowd control unit 11. The learning unit 19 receives actual network data from the crowd control unit 11 and accumulates the received actual network data.

[0084] Further, the learning unit 19 calculates a prediction model for predicting future actual network data using past actual network data. The learning unit 19 may calculate the prediction model during a time period when no passengers occur, such as at night. Also, the learning unit 19 may generate a prediction model for each day of the week or each time period. Further, the learning unit 19 may calculate the prediction model using machine learning such as deep learning. The learning unit 19 transmits the calculated prediction model to the crowd control unit 11.

[0085] The crowd control unit 11 creates actual network data based on the crowd data received from the robot 12. Also, each time the crowd control unit 11 creates actual network data, it transmits the actual network data to the learning unit 19.

[0086] The crowd control unit 11 acquires the prediction model from the learning unit 19. The crowd control unit 11 generates future actual network data based on the prediction model and the most recent actual network data. The crowd control unit 11 sets the control content of the robot 12 based on the future actual network data and transmits control data including the control content to the robot 12. Other operations of the crowd control unit 11 are the same as those in the first embodiment.

[0087] Based on the future actual network data received from the crowd control unit 11, the operation control unit 13 sets the operation control content and transmits operation control data including the operation control content to the elevator 14 or the landing call registration device 18. Other operations of the operation control unit 13 are the same as those in the first embodiment.

[0088] <D-2. Operations> FIG. 17 is a flowchart showing the operation of the crowd control unit 11 according to the fourth embodiment. Hereinafter, the operation of the crowd control unit 11 will be described along the flowchart of FIG. 17.

[0089] First, in step S601, the crowd control unit 11 acquires the prediction model from the learning unit 19. The acquisition timing of the prediction model is, for example, early morning when the learning unit 19 finishes calculating the prediction model.

[0090] Steps S602 to S604 after step S601 are the same as steps S101 to S103 in FIG. 7.

[0091] After step S604, in step S605, the crowd control unit 11 transmits the actual network data to the learning unit 19.

[0092] Next, in step S606, the crowd control unit 11 creates future actual network data based on the prediction model and the most recent actual network data. The crowd control unit 11 inputs the most recent actual network data created in step S604 into the prediction model acquired in step S601 and acquires future actual network data as the output of the prediction model.

[0093] Subsequently, in step S607, the pedestrian flow control unit 11 sets the control content for the robot 12 based on the future actual network data created in step S606. For example, if there are congested nodes in the future actual network data, the pedestrian flow control unit 11 sets the control content to move the robot 12 to the congested node. Alternatively, as explained in steps S104 to S106 of Figure 7, the pedestrian flow control unit 11 may transmit the future actual network data to the operation control unit 13 and set the content of the pedestrian flow control in response to the pedestrian flow control request received from the operation control unit 13.

[0094] Next, in step S608, the pedestrian flow control unit 11 transmits control data, including the control content set in step S607, to the robot 12.

[0095] Figure 18 is a flowchart showing the operation of the operation control unit 13 according to Embodiment 4. The operation of the operation control unit 13 will be described below in accordance with the flow shown in Figure 18.

[0096] Steps S701 to S703 are the same as steps S201 to S203 in Figure 8.

[0097] After step S703, in step S704, the operation control unit 13 acquires future actual network data from the passenger flow control unit 11.

[0098] Next, in step S705, the operation control unit 13 sets the operation control content based on future actual network data. For example, if the number of people present at the elevator hall 15 node is large in the future actual network data, the operation control unit 13 changes the settings to an operation control content that has the necessary number of passengers to transport for that number of people. Also, if the number of people present at the landing call registration device 18 node is large, the operation control unit 13 sets the operation control content to change the number of landing call registration devices 18 so that the waiting time for that number of people is less than or equal to a certain amount.

[0099] After that, in step S706, the operation control unit 13 transmits control data including the operation control content to the elevator 14 or the landing call registration device 18. Thus, the processing of the operation control unit 13 ends.

[0100] FIG. 19 is a flowchart showing the operation of the learning unit 19 according to the fourth embodiment. Hereinafter, the operation of the learning unit 19 will be described along the flowchart of FIG. 19.

[0101] First, in step S801, the learning unit 19 receives and accumulates the actual network data created by the crowd flow control unit 11 at any time.

[0102] Next, in step S802, the learning unit 19 determines whether it is necessary to calculate the prediction model. For example, the learning unit 19 determines whether the current time is in the night time zone, and if it is in the night time zone, it determines to calculate the prediction model. Note that the calculation time of the prediction model is not limited to night, and any time zone where sufficient computing resources can be secured is acceptable.

[0103] If it is determined in step S802 that the prediction model is not to be calculated, the processing of the learning unit 19 ends.

[0104] If it is determined in step S802 that the prediction model is to be calculated, in step S803, the learning unit 19 calculates the prediction model. For example, the learning unit 19 uses the accumulated actual network data as input and creates a prediction model for predicting future actual network data by deep learning.

[0105] Next, in step S804, the learning unit 19 transmits the calculated prediction model to the crowd flow control unit 11.

[0106] In this embodiment, since the crowd flow control unit 11 creates future actual network data based on the prediction model, it is possible to perform crowd flow control and operation control in advance so that congestion does not occur in the elevator hall 15 or the like.

[0107] <D-3. Effects> In the elevator system 104 according to Embodiment 4, the crowd control unit 11 predicts future actual network data from the actual network data created based on the crowd data measured by the robot 12, and determines the content of crowd control based on the future actual network data. Thereby, it is possible to predict the future congestion situation and quickly perform crowd control.

[0108] <E. Embodiment 5> <E-1. Configuration> FIG. 20 is a configuration diagram of the facility plan creation device 105 according to Embodiment 5. The facility plan creation device 105 includes a simulation unit 30 and a facility design unit 35. The simulation unit 30 includes a crowd control unit 31, a virtual robot 32, an operation control unit 33, and a virtual elevator 34, and is a virtual configuration of the elevator system 101 according to Embodiment 1 by an information terminal such as a personal computer. The crowd control unit 31 and the operation control unit 33 have the same functions as the crowd control unit 11 and the operation control unit 13 in Embodiment 1. The virtual robot 32 is a virtual configuration of the robot 12 in Embodiment 1 by an information terminal. The virtual elevator 34 is a virtual configuration of the elevator 14 in Embodiment 1 by an information terminal. Alternatively, the simulation unit 30 may be a virtual configuration of any one of the elevator systems 102-104 according to Embodiments 2-4 by an information terminal such as a personal computer.

[0109] The Equipment Design Department 35 is comprised of information terminals such as personal computers and sets the specifications for the elevator system 101. The specifications for the elevator system 101 include elevator specifications (specifications for elevators 14), building specifications (specifications for the building in which elevators 14 are installed), robot specifications (specifications for robots 12), and design standard specifications. The building specifications include the number of floors, floor height, floor layout, and floor use. The elevator specifications include the arrangement, number, and function of elevators 14. The design standard specifications include the required transport efficiency and budget. The robot specifications include the number and function of robots 12. The Equipment Design Department 35 determines the building specifications and design standard specifications based on information manually entered by the user of the information terminal.

[0110] The simulation unit 30 receives specification data defining the specifications of the elevator system 101 and passenger data from the equipment design unit 35. The passenger data is, for example, the time-series network data described in Embodiment 1, which shows the number of people present at each node of the building and the number of people moving between nodes in a time series. The simulation unit 30 performs a simulation based on the data received from the equipment design unit 35 and transmits the simulation results to the equipment design unit 35. The simulation results include time-series network data during the simulation period.

[0111] The equipment design department 35 determines whether the simulation results received from the simulation department 30 meet the design standard specifications. The determination criteria are, for example, whether the average waiting time of passengers obtained by statistical processing from the simulation results is less than or equal to the average waiting time defined in the design standard specifications. If the simulation results do not meet the design standard specifications, the equipment design department 35 changes the elevator specifications and robot specifications and transmits these specifications to the simulation department 30. In the simulation department 30, a simulation is performed using the changed elevator specifications and robot specifications, and the simulation results are transmitted to the equipment design department 35. The equipment design department 35 repeats the change of the elevator specifications and robot specifications until the simulation results meet the design standard specifications. In this way, the equipment design department 35 changes the elevator specifications and robot specifications for the building specifications so as to meet the design standard specifications.

[0112] When the simulation results meet the design standard specifications, the equipment design department 35 displays the elevator specifications, robot specifications, and simulation results on the output screen of the information terminal or the like.

[0113] <E-2. Operation> FIG. 21 is a flowchart showing the operation of the equipment design department 35 according to Embodiment 5. Hereinafter, the operation of the equipment design department 35 will be described along the flow of FIG. 21.

[0114] First, in step S901, the equipment design department 35 sets the building specifications. The equipment design department 35 receives an input from the user of the information terminal and sets the building specifications based on the input information. The building specifications may be represented by bim data or cad data.

[0115] Next, in step S902, the equipment design department 35 sets the design standard specifications. The equipment design department 35 receives an input from the user of the information terminal and sets the design standard specifications based on the input information.

[0116] Subsequently, in step S903, the equipment design department 35 determines the elevator specifications in relation to the building specifications and design standard specifications. If the simulation results do not meet the design standard specifications and the elevator specifications need to be set again, the equipment design department 35 sets the elevator specifications based on the results of the previous simulations. For example, if the average waiting time for passengers in the previous simulation was poor, and the average waiting time for passengers in the simulation before that was too good, the equipment design department 35 increases the number of elevator cars in the elevator specifications to a range less than the number of elevator cars in the elevator specifications before that.

[0117] Next, in step S904, the equipment design unit 35 sets the robot specifications for the building specifications, design standard specifications, and elevator specifications. If the simulation results do not meet the design standard specifications and the robot specifications need to be set again, the equipment design unit 35 sets the robot specifications based on the results of the previous simulations. For example, if the passenger waiting time in the previous simulation was poor, and the average passenger waiting time in the simulation before that was too good, the equipment design unit 35 increases the number of robots in the robot specifications to a range less than the number of robots in the robot specifications before that.

[0118] Subsequently, in step S905, the equipment design unit 35 transmits the specifications set in steps S901 to S904 to the simulation unit 30. The simulation unit 30 then simulates the operation of the elevator system 101 based on the specifications received from the equipment design unit 35.

[0119] Next, in step S906, the equipment design unit 35 receives the simulation results from the simulation unit 30.

[0120] After that, in step S907, the facility design department 35 determines whether the simulation results meet the design standard specifications. When the simulation results are close to the conditions set in the design standard specifications, the facility design department 35 determines that the simulation results meet the design standards. The facility design department 35 may focus on the average waiting time of passengers in the elevator hall 15 and determine whether the simulation results meet the design standard specifications. For example, if the average waiting time is set to 30 seconds or less in the design standard specifications, but the average waiting time in the simulation results is 10 seconds with 7 elevators, the elevator specifications and robot specifications are excessive compared to the design standard specifications. Therefore, the facility design department 35 may change the elevator specifications so that the average waiting time becomes worse. Suppose the average waiting time in the simulation results is 25 seconds when the number of elevators is 6, and the average waiting time in the simulation results is 40 seconds when the number of elevators is 5. In this case, the facility design department 35 determines that the facility standard specifications are met when the number of elevators is 5.

[0121] If the simulation results do not meet the design standards in step S907, the process of the facility design department 35 returns to step S903. That is, based on the comparison result between the simulation results and the design standard specifications required for the elevator system, the facility design department 35 changes the facility design data and inputs it to the simulation department 30.

[0122] If the simulation results meet the design standards in step S907, in step S908, the facility design department 35 outputs the simulation results that meet the design standard specifications to the screen of the information terminal.

[0123] <E-3. Effect> The facility plan creation device 105 according to Embodiment 5 includes a simulation unit 30 that simulates the processing of an elevator system, and a facility design unit 35 that determines the specifications of the elevator system. The elevator system is any one of the elevator systems according to Embodiments 1 to 4. The facility design unit 35 inputs facility design data including the specifications of passengers, elevators, and robots generated by the simulation to the simulation unit 30, and the simulation unit 30 simulates the processing of the elevator system based on the facility design data. By virtually controlling elevators and robots in a building on an information terminal, it is possible to evaluate the flow of people in the building and propose a facility plan including elevator specifications and robot specifications that meet the customer's requirements.

[0124] <F. Hardware Configuration> The people flow control unit 11, operation control unit 13, virtual robot 32, and virtual elevator 34 in the above-described elevator systems 101-104 and facility plan creation device 105 are realized by a processing circuit 81 shown in FIG. 22. That is, the processing circuit 81 includes a people flow control unit 11, an operation control unit 13, a virtual robot 32, and a virtual elevator 34 (hereinafter referred to as "the people flow control unit 11, etc."). Dedicated hardware may be applied to the processing circuit 81, or a processor that executes a program stored in a memory may be applied. The processor is, for example, a central processing unit, a processing device, an arithmetic device, a microprocessor, a microcomputer, a DSP (Digital Signal Processor), or the like.

[0125] If the processing circuit 81 is dedicated hardware, it may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination thereof. Each function of the pedestrian flow control unit 11, etc., may be implemented by multiple processing circuits 81, or the functions of each part may be implemented together by a single processing circuit.

[0126] When the processing circuit 81 is a processor, the functions of the pedestrian flow control unit 11, etc., are realized by a combination of software, firmware, or software and firmware. The software, etc., is written as a program and stored in memory. As shown in Figure 23, the processor 82 applied to the processing circuit 81 realizes the functions of each part by reading and executing the program stored in memory 83. In other words, the elevator systems 101-104 and the equipment planning device 105 are equipped with memory 83 for storing a program that, when executed by the processing circuit 81, will result in the execution of each function of the elevator systems 101-104 and the equipment planning device 105. In other words, this program can be said to cause the computer to execute the procedures or methods of the pedestrian flow control unit 11, etc. Here, memory 83 may be, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), HDD (Hard Disk Drive), magnetic disk, flexible disk, optical disk, compact disk, minidisc, DVD (Digital Versatile Disk) and its drive device, or any storage medium that may be used in the future.

[0127] The above describes a configuration in which each function of the pedestrian flow control unit 11, etc., is realized by either hardware or software. However, this is not the only configuration; a configuration in which part of the pedestrian flow control unit 11, etc., is realized by dedicated hardware and another part is realized by software, etc. For example, the pedestrian flow control unit 11 can be realized by a processing circuit as dedicated hardware, while the other functions can be realized by a processing circuit 81 as a processor 82 that reads and executes a program stored in memory 83.

[0128] As described above, the processing circuit can realize each of the above-mentioned functions through hardware, software, or a combination thereof.

[0129] Furthermore, it is possible to freely combine the embodiments, and to modify or omit the embodiments as appropriate. The above description is illustrative in all embodiments. It is understood that countless variations not illustrated are conceivable. [Explanation of symbols]

[0130] 11. Passenger flow control unit, 12, 12A, 12B, 12C. Robots, 13. Operation control unit, 14. Elevator, 15. Elevator hall, 16. Corridor, 17A, 17B. Routes, 18. Landing call registration device, 19. Learning unit, 30. Simulation unit, 31. Passenger flow control unit, 32. Virtual robot, 33. Operation control unit, 34. Virtual elevator, 35. Equipment design unit, 51, 52, 53. Nodes, 61, 62, 63. Edges, 81. Processing circuit, 82. Processor, 83. Memory, 101-104. Elevator system, 105. Equipment planning device.

Claims

1. A robot that autonomously moves through a building equipped with elevators having multiple cages and measures pedestrian flow data around itself using a measuring device mounted on it, The system includes a human flow control unit that causes the robot to perform human flow control, which is the control of the flow of people heading towards the elevator, based on human flow data measured by the robot and the operation data of the elevator. The pedestrian flow control unit determines a designated location where the robot should next measure pedestrian flow data, based on the pedestrian flow data measured by the robot. The robot measures the pedestrian flow data at the designated location. Elevator system.

2. A robot that autonomously moves through a building equipped with elevators having multiple cages and measures pedestrian flow data around itself using a measuring device mounted on it, The system includes a human flow control unit that causes the robot to perform human flow control, which is the control of the flow of people heading towards the elevator, based on human flow data measured by the robot and the operation data of the elevator. The system further includes an operation control unit that controls the operation of the elevator and outputs the operation data of the elevator to the passenger flow control unit, The operation control of the elevator includes controlling the number of landing call registration devices installed in the elevator hall. Elevator system.

3. A robot that autonomously moves through a building equipped with elevators having multiple cages and measures pedestrian flow data around itself using a measuring device mounted on it, The system includes a human flow control unit that causes the robot to perform human flow control, which is the control of the flow of people heading towards the elevator, based on human flow data measured by the robot and the operation data of the elevator. The system further includes an operation control unit that controls the operation of the elevator and outputs the operation data of the elevator to the passenger flow control unit, The pedestrian flow control unit creates actual network data representing the pedestrian flow within the building based on the pedestrian flow data measured by the robot. The actual network data includes a plurality of nodes representing locations within the building, and edges connecting two of the nodes where a person can move. The value of the node represents the number of people present at the location represented by the node. The weight of the edge represents the number of people who move between the two nodes at both ends of the edge per unit time. Elevator system.

4. The aforementioned pedestrian flow control unit determines that any node whose congestion level is above a predetermined threshold is a congested node. The aforementioned pedestrian flow control includes restricting the inflow of people into the congested node, The elevator system according to claim 3.

5. The operation control unit calculates the number of passengers getting on and off the elevator on each floor based on the operation data. The pedestrian flow control unit creates the actual network data based on the pedestrian flow data measured by the robot and the number of people getting on and off the elevator. The elevator system according to claim 3.

6. The pedestrian flow control unit predicts future real network data from the real network data created based on the pedestrian flow data measured by the robot, and determines the content of the pedestrian flow control based on the future real network data. The elevator system according to claim 3.

7. The operation control unit controls the operation of the elevator based on the future actual network data. The elevator system according to claim 6.

8. The system further includes a learning unit that stores past real network data created by the human flow control unit based on human flow data measured by the robot, and learns a predictive model to predict future real network data based on the stored past real network data. The pedestrian flow control unit creates the future actual network data based on the most recent actual network data and the prediction model. The elevator system according to claim 6.

9. A simulation unit that simulates the processing of the elevator system, A facility planning device comprising a facility design unit for determining the specifications of the elevator system, The elevator system is A robot that autonomously moves within a building equipped with elevators having multiple cages and measures pedestrian flow data around itself using a measuring device mounted on it, The system includes a pedestrian flow control unit that causes the robot to control the flow of people to the elevator based on pedestrian flow data measured by the robot and elevator operation data, The equipment design unit inputs equipment design data, including the passenger specifications generated in the simulation, the elevator specifications, and the robot specifications, into the simulation unit. The simulation unit simulates the processing of the elevator system based on the equipment design data. Equipment planning device.

10. The equipment design unit acquires the simulation results from the simulation unit, modifies the equipment design data based on the comparison results between the simulation results and the design standard specifications required for the elevator system, and inputs the modified data into the simulation unit. The equipment planning device according to claim 9.

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