Management system, management device, control method for management device, program, inference device, learning device, and information processing device.

Abstract

This system provides an elevator management system that can provide appropriate notifications, taking into account the needs of the passengers inside the elevator car, when both the passengers and the moving object are inside the elevator car. [Solution] The management system 1 comprises an elevator 2, a mobile elevator 3, and a management device 5. The planning unit 56 plans either the disembarking route or the passage area for the person who will get off the car 20 first among the users in the mobile elevator 3 and car 20, when at least one user is in the car 20 on which the mobile elevator 3 is riding and a destination floor different from the destination floor of the mobile elevator 3 is registered. The notification unit 33 notifies the person who will get off the car 20 first among the users in the mobile elevator 3 and car 20 of the plan planned by the planning unit 56 via an alarm so that other users in the mobile elevator 3 and car 20 can recognize it.

Description

Technical Field

[0001] The present disclosure relates to a management system, a management device, a control method for a management device, a program, an inference device, a learning device, and an information processing device.

Background Art

[0002] Patent Document 1 describes an elevator interlocking system. The interlocking system described in Patent Document 1 includes a robot management system. The robot management system manages a robot that moves between floors while riding in an elevator car. The robot receives list information indicating the boarding status of the car from an elevator control system. When the car arrives at the landing, the robot determines whether it is possible to board the car based on the received list information.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The present disclosure has been made to solve the above problems. An object of the present disclosure is to provide a management system, a management device, and a control method for a management device that can perform appropriate notification considering the user in the car when a user and a moving body are in an elevator car. Another object of the present disclosure is to provide a program for realizing such a function on a computer. Another object of this disclosure is to provide an inference device for inferring either the disembarking route or the passage area of ​​a person who disembarks from a car the fastest, and a learning device for learning either the disembarking route or the passage area, which can be used to realize such a function. Another object of this disclosure is to provide an information processing device for outputting notification content, etc., which can be used when realizing such a function. [Means for solving the problem]

[0006] The management system relating to this disclosure comprises an elevator having a car, a mobile body that autonomously moves within a facility equipped with an elevator, and a management device capable of communicating with the elevator and the mobile body. The management system includes an alarm, a planning unit that plans either a disembarking route or a passage area for the person who will disembark first from the car among the users in the mobile body and car when at least one user is in the car on which the mobile body is riding and a destination floor different from the destination floor of the mobile body is registered, and the planning unit that uses the one planned by the planning unit for the users in the mobile body and car other than the person concerned. use It includes a notification unit that notifies the person in question via an alarm so that the person can recognize it.

[0007] The management device relating to this disclosure is a management device capable of communicating with an elevator having a car and a mobile body that moves autonomously within a facility equipped with an elevator. The management device comprises a planning unit that plans either the disembarking route or the passage area of ​​the person who will get off the car first among the users in the mobile body and car, when at least one user is in the car in which the mobile body is riding and a destination floor different from the destination floor of the mobile body is registered, and a communication unit that transmits a notification to the mobile body so that the one planned by the planning unit can be recognized by users in the mobile body and car other than the person concerned.

[0008] The control method for the management device relating to this disclosure is a control method for a management device that can communicate with an elevator having a car and a mobile body that moves autonomously within a facility equipped with an elevator. The control method comprises a planning step of planning either the disembarking route or the passage area of ​​the person who will get off the car first among the users in the mobile body and car, when at least one user is in the car in which the mobile body is riding and a destination floor different from the destination floor of the mobile body is registered, and a communication step of transmitting a notification to the mobile body so that the one planned in the planning step can be recognized by users in the mobile body and car other than the person concerned.

[0009] The program relating to this disclosure is a program that causes a computer capable of communicating with an elevator having a car and a mobile body that autonomously moves within a facility equipped with an elevator to execute a planning process that plans either the disembarking route or the passage area of ​​the person who will get off the car first among the users in the mobile body and car, when at least one user is in the car in which the mobile body is riding and a destination floor different from the destination floor of the mobile body is registered, and a communication process that sends a notification to the mobile body so that the one planned in the planning process can be recognized by users in the mobile body and car other than the person in question.

[0010] The inference device relating to this disclosure comprises a data acquisition unit that acquires inference data, and an inference unit that uses a trained model to infer either the disembarking route or the passage area of ​​a subject in an elevator car from the inference data, and outputs one of the two from the inference data acquired by the data acquisition unit. The subject is the person who disembarks first from the elevator car when at least one user is in the elevator car carrying a mobile body that moves autonomously within a facility equipped with an elevator, and a destination floor different from the destination floor of the mobile body is registered. The inference data includes the destination floor of the mobile body, the destination floor of the user in the elevator car, and an image taken inside the elevator car, or the positions of the mobile body and user inside the elevator car.

[0011] The learning device relating to this disclosure comprises a data acquisition unit that acquires training data, and a model generation unit that uses the training data acquired by the data acquisition unit to generate a trained model for inferring either the disembarking route or the passage area of ​​a target person in an elevator car. The target person is the person who disembarks first from the elevator car when at least one user is in the elevator car carrying a mobile body that moves autonomously within a facility equipped with an elevator, and a destination floor different from the destination floor of the mobile body is registered. The training data includes the destination floor of the mobile body, the destination floor of the user in the car, and either an image taken inside the car or the positions of the mobile body and the user inside the car. The trained model is a model for inferring either the destination floor of the mobile body or the destination floor of the user in the car and an image or position.

[0012] The information processing device relating to this disclosure comprises a data acquisition unit that acquires input data, and a control unit that acquires and outputs output data by inputting the input data acquired by the data acquisition unit into artificial intelligence. The input data includes either the disembarking route or the area of ​​passage of the subject. The subject is the person who disembarks first from the elevator car of an autonomously moving vehicle in a facility equipped with an elevator, when at least one user is in the elevator car and a destination floor different from the destination floor of the vehicle is registered. The output data includes notification content for notifying the person in the elevator car. [Effects of the Invention]

[0013] According to this disclosure, when a user and a moving object are in the elevator car, appropriate notification can be provided that takes into account the user inside the car. [Brief explanation of the drawing]

[0014] [Figure 1] This figure shows an example of a management system in Embodiment 1. [Figure 2] This flowchart shows an example of the operation of the control device. [Figure 3]It is a flowchart showing an operation example of a moving body. [Figure 4] It is a flowchart showing another operation example of a moving body. [Figure 5] It is a flowchart showing a determination example of an operation performed by a moving body. [Figure 6] It is a diagram showing an example of an inference device. [Figure 7] It is a flowchart showing an operation example of an inference device. [Figure 8] It is a diagram showing an example of a learning device. [Figure 9] It is a diagram showing an example of a neural network applied to a learning device. [Figure 10] It is a flowchart showing an operation example of a learning device. [Figure 11] It is a diagram showing an example of an information processing device. [Figure 12] It is a flowchart showing an operation example of an information processing device. [Figure 13] It is a diagram showing an example of the hardware resources of a management device. [Figure 14] It is a diagram showing another example of the hardware resources of a management device.

Embodiment for Carrying Out the Invention

[0015] Hereinafter, a detailed description will be given with reference to the drawings. Redundant descriptions will be appropriately simplified or omitted. In each figure, the same reference numerals indicate the same or corresponding parts.

[0016] Embodiment 1. FIG. 1 is a diagram showing an example of a management system 1 in Embodiment 1. In the example shown in FIG. 1, the management system 1 includes an elevator 2, a moving body 3, peripheral devices 4, and a management device 5.

[0017] The elevator 2 is provided in Facility A. Facility A includes one or more buildings. Facility A may be an indoor facility or an outdoor facility.

[0018] Elevator 2 comprises a car 20 and a control device 21. The car 20 moves up and down in the hoistway. The hoistway is a vertically extending space formed in the building of Facility A. The hoistway is formed to penetrate multiple floors of the building. Figure 1 shows a preferred example in which elevator 2 comprises multiple cars 20. Elevator 2 may also consist of only one car 20.

[0019] The elevator car 20 may be equipped with an alarm device 22. The alarm device 22 is a device for providing information to passengers riding in the elevator car 20. The alarm device 22 may be a device that displays text or other information, or a device that outputs sound. The elevator car 20 may be equipped with both a display and a speaker as the alarm device 22. The elevator car 20 may be equipped with a projector as the alarm device 22.

[0020] The elevator car 20 may be equipped with a weighing device 23. The weighing device 23 measures the load weight of the elevator car 20. The elevator car 20 may be equipped with a camera 24. The camera 24 photographs the inside of the elevator car 20. If there is a passenger in the elevator car 20, that passenger will be photographed by the camera 24. The elevator car 20 may be equipped with a door sensor 25. The door sensor 25 is, for example, a multi-beam sensor. When the door of the elevator car 20 is open, if an object present at the entrance of the elevator car 20 obstructs the beam from the door sensor 25, the door sensor 25 detects the presence of an object at the entrance of the elevator car 20.

[0021] The weighing device 23, camera 24, and door sensor 25 are examples of detectors provided on the cage 20. Other devices may be provided on the cage 20 as detectors.

[0022] The control device 21 manages the operation of the elevator car 20. The control device 21 controls the movement of the elevator car 20. If the elevator 2 is equipped with multiple elevator cars 20, the control device 21 manages the multiple elevator cars 20 as a group.

[0023] The control device 21 manages the equipment installed in the elevator car 20. For example, the alarm 22 and the door sensor 25 are controlled by the control device 21. The measurement results from the weighing device 23, the images captured by the camera 24, and the detection results from the door sensor 25 are input to the control device 21. In the example shown in Figure 1, the control device 21 also controls the communication functions in the elevator 2.

[0024] Mobile unit 3 moves autonomously within facility A. For example, mobile unit 3 is a cleaning robot. Mobile unit 3 may also be a security robot. Mobile unit 3 may also be a robot for transporting goods. Mobile unit 3 may also be a robot that performs other roles within facility A. Mobile unit 3 can move to a desired floor within facility A by riding in the cage 20. That is, mobile unit 3 can autonomously board the cage 20 and disembark from the cage 20.

[0025] At facility A, the mobile vehicle 3 can travel together with the user in the car 20. The mobile vehicle 3 may board the car 20 that a user is already in. The user may board the car 20 that the mobile vehicle 3 is already in.

[0026] The mobile unit 3 comprises an alarm 30, a detector 31, and a control unit 32. The alarm 30 is a device for providing information to users in the vicinity of the mobile unit 3. The alarm 30 may be a device that displays text or other information, or a device that outputs sound. The mobile unit 3 may be equipped with both a display and a speaker as the alarm 30. The mobile unit 3 may be equipped with a projector as the alarm 30.

[0027] The detector 31 is a device for detecting the surrounding conditions of the mobile body 3. These surrounding conditions include the conditions of users around the mobile body 3. The mobile body 3 may be equipped with a proximity sensor or a LiDAR sensor as the detector 31. The mobile body 3 may be equipped with a camera as the detector 31. The mobile body 3 may be equipped with other devices as the detector 31.

[0028] The control unit 32 performs various controls on the mobile unit 3. The control unit 32 controls the movement of the mobile unit 3. Boarding and alighting from the cage 20 of the mobile unit 3 is controlled by the control unit 32. The control unit 32 manages the equipment installed on the mobile unit 3. The alarm 30 is controlled by the control unit 32. Detection results from the detector 31 are input to the control unit 32. In the example shown in Figure 1, the control unit 32 also manages the communication function of the mobile unit 3. The control unit 32 includes an alarm unit 33, a route determination unit 34, and a movement control unit 35.

[0029] Peripheral equipment 4 is a general term for the equipment installed in facility A. Peripheral equipment 4 includes alarms 40 and detectors 41. Alarms 40 are devices for providing information to users in the vicinity. Alarms 40 may be devices that display text, etc., or devices that output sound. At the landing where elevator car 20 of elevator 2 stops, both a display and a speaker may be installed as alarms 40. At the landing, a projector may be installed as alarms 40. Alarms 40 may be installed in elevator car 20 of elevator 2 as an alarm separate from alarms 22 managed by elevator 2.

[0030] The detector 41 is a device for detecting the surrounding conditions. These surrounding conditions include the conditions of users in the vicinity of the detector 41. A proximity sensor or LiDAR sensor may be installed as the detector 41 at the landing where the elevator car 20 of elevator 2 stops. A camera may be installed as the detector 41 at the landing. Other devices may be installed as the detector 41 at the landing. The elevator car 20 of elevator 2 may also be equipped with a detector 41 separate from the detectors managed by elevator 2.

[0031] The control device 5 can communicate with the elevator 2, the mobile unit 3, and the peripheral equipment 4. For example, the control device 5 is installed in facility A.

[0032] The control device 5 may be located remotely from facility A. In this case, the control device 5 is connected to the elevator 2, the mobile unit 3, and the peripheral equipment 4 via a communication network. This communication network is a wide-area communication network such as the Internet. This communication network may also be a VPN (Virtual Private Network) formed on a public network such as the Internet, or another secure network.

[0033] For example, the management device 5 is implemented on an on-premise server of a maintenance company that maintains elevator 2 or a management company that manages mobile unit 3. The management device 5 may be implemented using multiple servers. If the management device 5 is implemented using multiple servers, some servers may be located at facility A, and the remaining servers may be located remotely. As another example, the management device 5 may be implemented on a cloud server.

[0034] The management device 5 comprises a storage unit 50, a first communication unit 51, a second communication unit 52, a third communication unit 53, and a processing unit 54.

[0035] The first communication unit 51 has the function of communicating with the mobile body 3. The second communication unit 52 has the function of communicating with the peripheral device 4. The third communication unit 53 has the function of communicating with the elevator 2. The processing unit 54 includes an acquisition unit 55, a planning unit 56, and a notification unit 57.

[0036] Next, referring to Figures 2 and 3, the functions of the management system 1 will be explained in detail. Figure 2 is a flowchart showing an example of the operation of the management device 5. The management device 5 determines whether or not the moving object 3 has entered the elevator car 20 of the elevator 2 (S101).

[0037] Figure 3 is a flowchart illustrating an example of the operation of the mobile unit 3. As described above, the mobile unit 3 moves autonomously within facility A. When the mobile unit 3 needs to move by riding in the cage 20, the control unit 32 sends a call registration request to the management device 5 (S201). Hereafter, the mobile unit 3 that sent the call registration request in S201 will also be referred to as mobile unit 3A to distinguish it from other mobile units 3. As an example, the call registration request includes identification information to identify mobile unit 3A, information on the boarding floor F1 of mobile unit 3A, and information on the destination floor F2 of mobile unit 3A.

[0038] In mobile unit 3A, when a call registration request is sent in S201, it is determined whether or not a boarding request has been received from the management device 5 as a response (S202). When car 20 responds to the call registration request sent from mobile unit 3A in S201 and car 20 arrives at boarding floor F1, a boarding request is sent from the first communication unit 51 of the management device 5 to mobile unit 3A. When the control unit 32 receives this boarding request, it is determined to be Yes in S202. If it is determined to be Yes in S202, the control unit 32 controls the drive unit (not shown) so that mobile unit 3A boards car 20 (S203). Hereafter, car 20, which mobile unit 3A boarded from boarding floor F1, will also be referred to as car 20C.

[0039] It is desirable that the presence of the mobile body 3A in the car 20C be recognized by the elevator 2, the mobile body 3A, and the control device 5. Detection of the mobile body 3A being in the car 20C is possible by the detector 31 on the mobile body 3A, the detector 41 as a peripheral device 4, and the detector on the car 20C. This detection may be performed by each detector or by a single detector.

[0040] For example, when the detector in car 20C detects that the mobile body 3A has boarded, the control device 21 sends a boarding completion notification to the management device 5, and this notification is further transmitted from the first communication unit 51 to the mobile body 3A. In another example, when the detector 31 in mobile body 3 detects that the mobile body 3A has boarded, the control unit 32 sends a boarding completion notification to the management device 5, and this notification is further transmitted from the third communication unit 53 to the elevator 2. The management device 5 recognizes that the mobile body 3A has boarded car 20C, and determines Yes in S101.

[0041] If the answer in S101 is "Yes", the management device 5's acquisition unit 55 acquires the usage information D for the cage 20C (S102). The usage information D includes usage information related to the mobile body 3A and usage information related to the user.

[0042] As an example, usage information D includes information on the destination floor F2 of the mobile unit 3A and information on the destination floor of the user riding in the car 20C. Hereafter, the destination floor of the user riding in the car 20C will also be referred to as destination floor F3. For example, when the control device 21 of elevator 2 recognizes that the mobile unit 3A has entered the car 20C, it transmits the destination floor information registered for the car 20C to the management device 5. This information includes information on the destination floor F2 of the mobile unit 3A. If there is a user in the car 20C, this information also includes information on the destination floor F3 of that user. In S102, the acquisition unit 55 acquires this information received by the third communication unit 53 from the control device 21 as usage information D.

[0043] The acquisition unit 55 may acquire usage information D from the storage unit 50 in S102. The storage unit 50 stores the contents of communications between the management device 5 and the mobile unit 3A, the contents of communications between the management device 5 and the peripheral equipment 4, and the contents of communications between the management device 2 and the elevator 2. If the control device 21 periodically transmits the destination floor information registered for each car 20 to the management device 5, the acquisition unit 55 may acquire usage information D from the storage unit 50 in S102.

[0044] As another example, the usage information D may include information indicating the position of the moving object 3A inside the car 20C, and information indicating the position of the user inside the car 20C. If the car 20C is equipped with a proximity sensor or LiDAR sensor as a detector, the control device 21 transmits the detection result from the sensor to the management device 5. In S102, the acquisition unit 55 may acquire the detection result received by the third communication unit 53 from the control device 21 as usage information D.

[0045] If the mobile body 3A is equipped with a proximity sensor or LiDAR sensor as a detector 31, the control unit 32 of the mobile body 3A may transmit the detection result from the sensor to the management device 5 when it recognizes that the mobile body 3A has boarded the cage 20C. In this case, the acquisition unit 55 may acquire the detection result received by the first communication unit 51 from the mobile body 3A as usage information D in S102.

[0046] As another example, the usage information D may include images taken inside the elevator car 20C. If the elevator car 20C is equipped with a camera 24, the control device 21 transmits images taken by the camera 24 to the management device 5. In S102, the acquisition unit 55 may acquire the images received by the third communication unit 53 from the control device 21 as usage information D.

[0047] If the mobile body 3A is equipped with a camera as a detector 31, the control unit 32 of the mobile body 3A may transmit an image captured by the camera to the management device 5 when it recognizes that the mobile body 3A has boarded the cage 20C. In this case, the acquisition unit 55 may acquire the image received by the first communication unit 51 from the mobile body 3A as usage information D in S102.

[0048] As another example, user information D may include information indicating the mobility attributes of the user in cart 20C. User mobility attributes indicate the state of the user's movement. For example, user mobility attributes may include normal walking, carrying a suitcase, using a wheelchair, and using a stroller. Mobility attributes may also be values ​​indicating the difficulty of movement.

[0049] Next, the management device 5 determines whether or not a specific planning condition is met (S103). The planning condition is the condition for starting the planning process in S104, which will be described later. The planning condition is met when at least one user is in the car 20C on which the mobile body 3A is riding, and a destination floor different from the destination floor F2 of the mobile body 3A is registered for the car 20C.

[0050] For example, the planning condition is met if the mobile unit 3A boards car 20C which already has a passenger, and the destination floor F3 of this passenger does not match the destination floor F2. The planning condition is also met if a passenger later boards car 20C which mobile unit 3A is already in, and the destination floor F3 of this passenger does not match the destination floor F2. When the planning condition is met, the result is determined to be Yes in S103.

[0051] If the answer in S103 is Yes, the planning unit 56 plans either the disembarking route or the passage area for the subject (S104). The subject is the person who disembarks from the car 20C first among the users in the mobile vehicle 3A and the car 20C. This "person" may include the mobile vehicle 3A.

[0052] The disembarking route is the path a person takes within the elevator car 20C when they disembark from it. The disembarking route is preferably represented by a line connecting the starting point to the destination point. The passage area is the area a person travels through within the elevator car 20C when they disembark from it. The passage area is preferably represented by a figure with an area such as a circle or polygon.

[0053] The planning unit 56 may also plan both the passenger's disembarkation route and the passage area in S104. Below, an example in which the planning unit 56 plans the passenger's disembarkation route in S104 will be described. Detailed explanations of the example in which the planning unit 56 plans the passenger's passage area and the example in which it plans both the disembarkation route and the passage area will be omitted. It is preferable that the planning unit 56 uses a predefined algorithm for planning. The planning unit 56 performs the planning based on the usage information D acquired by the acquisition unit 55 in S102.

[0054] Next, the management device 5 transmits a plan notification (S105). The plan notification is a notification to inform people inside the car 20C, other than the person inside the car 20C, of ​​the contents planned by the planning unit 56 in S104. If either the person's disembarking route or the area to be traveled is planned in S104, the plan notification includes that one. If both the person's disembarking route and the area to be traveled are planned in S104, the plan notification includes both. In the example shown in this embodiment, the plan notification includes the disembarking route planned by the planning unit 56.

[0055] The notification of the plan made by the planning unit 56 may be made from the notification device 30 on the mobile unit 3A, or from the notification device 22 on the car 20C. If the car 20C is equipped with a notification device 40, the notification may be made from the notification device 40. The plan notification is transmitted to the notification device that makes the notification. A preferred example in which the notification is made from the notification device 30 on the mobile unit 3A will be described below. In this example, the first communication unit 51 transmits a plan notification to the mobile unit 3A in S105, which includes the disembarkation route planned by the planning unit 56.

[0056] In the mobile unit 3A, when a passenger boards the car 20C, it is determined whether or not a plan notification has been received from the management device 5 (S204). If the control unit 32 receives the plan notification transmitted from the management device 5 in S105, it is determined to be Yes in S204. If it is determined to be Yes in S204, the notification unit 33 causes the notification device 30 to announce the contents planned by the planning unit 56, which are included in the plan notification (S205). For example, the notification unit 33 causes the notification device 30 to announce the passenger's disembarking route so that persons other than the passenger in the car 20C can recognize it.

[0057] Next, the mobile unit 3A determines whether or not the person is a target (S206). If the next stop of car 20C is the destination floor F2, the result in S206 is Yes. If the next stop of car 20C is not the destination floor F2, the result in S206 is No. If the result in S206 is No, the process returns to S204.

[0058] If the result in S206 is Yes, the mobile unit 3A is then checked to determine whether or not it has received a disembarkation request (S207). When the elevator car 20 arrives at the destination floor F2, a disembarkation request is transmitted from the first communication unit 51 of the management device 5. When the control unit 32 receives this disembarkation request, the result in S207 is Yes. If the result in S207 is Yes, the control unit 32 controls the drive mechanism so that the mobile unit 3A disembarks from the elevator car 20C (S208). The control unit 32 moves the mobile unit 3A along the disembarkation route planned by the planning unit 56 in S104.

[0059] In the example shown in this embodiment, when the planning conditions are met in S103, the planning unit 56 plans at least one of the disembarking route or passage area for the person, and the details of the plan are communicated inside the car 20C. Therefore, in the example shown in this embodiment, when a user and a mobile body 3A are in the car 20C, appropriate communication can be provided that takes into account the user in the car 20C. As a result, both the mobile body 3C and the user can use the elevator 2 smoothly.

[0060] In order to determine whether the planning conditions are met, the user information D must include information on the destination floor F2 of the mobile vehicle 3A and information on the destination floor F3 of the users riding in the car 20C. The planning unit 56 can identify the target person based on the destination floors F2 and F3.

[0061] Preferably, the usage information D further includes information indicating the position of the moving body 3A inside the car 20C and information indicating the position of the user. That is, the planning unit 56 may perform the planning process of S104 based on the position of the moving body 3A inside the car 20C and the position of the user. In this example, the planning unit 56 can easily identify the starting point of the disembarking route.

[0062] The positions of the moving body 3A and the user within the car 20C can also be determined from images taken inside the car 20C. For this reason, the user information D may include images taken inside the car 20C. In other words, the planning unit 56 may perform the planning process in S104 based on images taken inside the car 20C.

[0063] The user information D may also include information indicating the movement attributes of the user in the car 20C. That is, the planning unit 56 may perform the planning process in S104 based on the movement attributes of the user in the car 20C. In this example, the planning unit 56 can also plan a disembarking route that minimizes the movement of users who have difficulty moving. The movement attributes of the user in the car 20C can also be identified from images taken inside the car 20C. Both the user's position and movement attributes may be identified from these images.

[0064] The following describes other functions that can be adopted by Management System 1. Management System 1 may adopt a combination of the following functions, if possible.

[0065] Figures 2 and 3 illustrate an example in which the notification unit 33 of the mobile unit 3 implements the function of notifying the plan contents from the planning unit 56. As another example, the notification function may be implemented by the notification unit 57 of the management device 5. This example is suitable when the plan contents from the planning unit 56 are notified by the notification device 22 or notification device 40.

[0066] Figure 4 is a flowchart showing another example of the operation of the mobile unit 3A. Figure 4 shows an alternative operation flow when No is determined in S206 of Figure 3. If the mobile unit 3A is not the target person, No is determined in S206 (S301). In this case, the target person is the user in the car 20C.

[0067] If a user in the car 20C is a target person, the route determination unit 34 determines the movement path of the moving body 3C within the car 20C when the target person alights from the car 20C (S302). If the planning unit 56 has planned the target person's alighting route, the route determination unit 34 determines the movement path of the moving body 3C so that the moving body 3C does not obstruct the alighting route. If the planning unit 56 has planned the target person's passage area, the route determination unit 34 determines the movement path of the moving body 3C so that the moving body 3C does not obstruct the passage area. If the planning unit 56 has planned both the target person's alighting route and passage area, the route determination unit 34 determines the movement path of the moving body 3C so that the moving body 3C does not obstruct either of them.

[0068] Next, the movement control unit 35 moves the mobile body 3C along the movement path determined by the route determination unit 34 in S302 (S303). The notification unit 33 may also notify the user inside the car 20C of the movement path as the mobile body 3C moves along the movement path so that the user inside the car 20C can recognize the movement path.

[0069] In this example, when a user disembarks from car 20C, their movement is not obstructed by the moving body 3C. Therefore, both the moving body 3C and the user can use elevator 2 smoothly.

[0070] In the example shown in this embodiment, it is preferable that the notification of the plan contents be made in a manner that makes it easy for the user in the car 20C to recognize the contents.

[0071] For example, the notification device 30 of the mobile unit 3 is capable of emitting light and projecting an image onto the floor, walls, or air of the car 20C. In such a case, the notification unit 33 notifies the contents of the plan made by the planning unit 56 inside the car 20C using light from the notification device 30. For example, the notification unit 33 may project the passenger's disembarking route onto the floor using light from the notification device 30. The notification unit 33 may indicate the passenger's disembarking route with multiple arrows using light from the notification device 30. The notification unit 33 may also indicate the space to be left open using light from the notification device 30. Notification using light may be performed in conjunction with the movement of the mobile unit 3.

[0072] As another example, the alarm 30 of the mobile unit 3 is capable of emitting sound. In such a case, the notification unit 33 notifies the passengers inside the car 20C of the plan details from the planning unit 56 by sound from the alarm 30. For example, the notification unit 33 may explain the passenger's disembarking route itself by sound from the alarm 30, or it may explain the space that should be left open. The voice notification may be performed in conjunction with the light notification.

[0073] Figure 5 is a flowchart showing an example of the actions to be performed by the mobile unit 3A. Figure 5 shows the operation flow after the mobile unit 3A is in the car 20C. As an example, the processes shown in S401-S403 and S405-S407 in Figure 5 are performed by the control device 5. The processes shown in S404 and S408-S411 are performed by the mobile unit 3A. As another example, all the processes shown in Figure 5 may be performed by the mobile unit 3A after it has obtained the necessary information from the control device 5.

[0074] As described above, in the management device 5, the acquisition unit 55 acquires the usage information D of the car 20C (S401). Next, the management device 5 determines whether or not a user is in the car 20C (S402). If a user is in the car 20C, S402 determines Yes. If a user is not in the car 20C, S402 determines No.

[0075] If the result in S402 is Yes, then it is determined in S403 whether or not the user's destination floor is registered. If the user operates the control panel (not shown) inside car 20C and registers the destination floor, then S403 is determined to be Yes. If the user has not registered the destination floor, then S403 is determined to be No.

[0076] For example, immediately after a passenger boards car 20C carrying mobile unit 3A, S403 determines it to be No. When S403 determines it to be No, mobile unit 3A waits at a location away from the control panel of car 20C (S404). After that, when the passenger registers their destination floor from the control panel of car 20C, S403 determines it to be Yes.

[0077] If the result in S403 is Yes, then it is determined in S405 whether the destination floor F2 of mobile unit 3A is registered by the user. If the destination floor F2 of mobile unit 3A is registered by the user, the result in S405 is Yes. If the destination floor F2 of mobile unit 3A is not registered by the user, the result in S405 is No.

[0078] If the result in S405 is No, then it is determined in S406 whether or not there are passengers who get off car 20C before mobile unit 3A. If there are passengers who get off car 20C before mobile unit 3A, that is, if the passenger's destination floor F3 matches the destination floor F2 of mobile unit 3A, then the result in S406 is Yes. If there are no passengers who get off car 20C before mobile unit 3A, then the result in S406 is No.

[0079] If the result in S405 or S406 is Yes, then it is determined whether or not there is a mobile vehicle 3A on the user's disembarking route (S407). If there is a mobile vehicle 3A on the user's disembarking route, the result in S407 is Yes. If there is no mobile vehicle 3A on the user's disembarking route, the result in S407 is No.

[0080] A "Yes" determination in S407 occurs when there is a passenger going to the same destination floor F2 as the mobile vehicle 3A, or when there is a passenger getting off before the mobile vehicle 3A, and the mobile vehicle 3A is blocking that passenger's disembarking route. In this case, the mobile vehicle 3A takes action to allow the passenger to disembark first (S408).

[0081] Specifically, the mobile unit 3A moves in a manner that deviates from the passenger's disembarking route. If the floor where the passenger disembarks is the destination floor F2, the mobile unit 3A disembarks from the car 20C after the passenger disembarks from the car 20C. If the floor where the passenger disembarks is not the destination floor F2, the mobile unit 3A waits inside the car 20C and disembarks from the car 20C after the car 20C arrives at the destination floor F2. When the mobile unit 3A is moving, it is preferable to notify other passengers using light or sound.

[0082] A "No" result in S407 occurs when there are passengers going to the same destination floor F2 as mobile unit 3A, or when there are passengers disembarking before mobile unit 3A, and mobile unit 3A is not blocking the passengers' disembarking route. In this case as well, mobile unit 3A will prioritize passengers' disembarkation. However, mobile unit 3A is not required to move in order to prioritize passengers' disembarkation.

[0083] If the floor to which the passenger alights is the destination floor F2, the mobile unit 3A alights from the car 20C after the passenger alights from the car 20C. If the floor to which the passenger alights is not the destination floor F2, the mobile unit 3A waits inside the car 20C and alights from the car 20C after the car 20C arrives at the destination floor F2. The mobile unit 3A notifies the passenger of the alighting route when the passenger alights and when the mobile unit 3A alights (S409). This notification is preferably made using light or sound.

[0084] In S406, the result is determined to be "No" if there is a passenger in car 20C, but the mobile unit 3A disembarks from car 20C before the passenger. In this case, when mobile unit 3A disembarks from car 20C at the destination floor F2, it announces the disembarking route (S410). This announcement is preferably made using light or sound.

[0085] S402 is judged as "No" when only the mobile unit 3A is on board car 20C. In this case, mobile unit 3A waits at a designated location inside car 20C and disembarks from car 20C at the destination floor F2 (S411). Since there are no passengers in car 20C, no disembarkation route is announced.

[0086] Some or all of the functions of the processing unit 54 described in this embodiment may be implemented by an inference device 6 as shown in Figure 6.

[0087] Figure 6 shows an example of an inference device 6. When the management system 1 includes an inference device 6, the inference device 6 may be included in the management device 5, or it may be provided as a separate device from the management device 5. When the management system 1 includes an inference device 6, the management system 1 further includes a trained model storage unit 61. The functions of the trained model storage unit 61 may be realized by the storage unit 50. The inference device 6 may be provided in a device that can communicate with the management device 5. This device may include a specific single server, a specific group of servers, a cloud server, etc. The trained model storage unit 61 may be provided in this device.

[0088] As an example, the inference device 6 infers at least one of the disembarking route or the passage area of ​​the subject within the car 20C. The inference device 6 may infer both the disembarking route and the passage area of ​​the subject. The inference device 6 may infer only the disembarking route of the subject, or only the passage area of ​​the subject. As described above, the subject is the person who disembarks first from the car 20C among the users in the mobile body 3A and car 20C when at least one user is in the car 20C on which the mobile body 3A is riding and a destination floor different from the destination floor F2 of the mobile body 3A is registered.

[0089] The inference device 6 shown in Figure 6 comprises a data acquisition unit 62 and an inference unit 63.

[0090] Inference data is input to the inference device 6. The data acquisition unit 62 acquires the inference data input to the inference device 6. The function of the data acquisition unit 62 may also be implemented by the acquisition unit 55.

[0091] As an example, the inference data may include information indicating the destination floor F2 of the moving vehicle 3A, information indicating the destination floor F3 of the passenger inside the elevator car 20C, and information indicating the positions of the moving vehicle 3A and the passenger inside the elevator car 20C. The inference data may also include information indicating the destination floor F2, information indicating the destination floor F3, and images taken inside the elevator car 20C.

[0092] The inference data may further include information indicating the movement attributes of the user in cart 20C. The inference data may further include information indicating the attributes of the user in cart 20C. These user attributes may include, for example, gender, age (age group), and occupation. The inference data is data that correlates multiple pieces of information.

[0093] The trained model is stored in the trained model storage unit 61. For example, this trained model is a model for inferring the disembarking route of a person in the elevator car 20C from inference data. In this example, the inference unit 63 uses the trained model stored in the trained model storage unit 61 to infer the disembarking route of the person from the inference data acquired by the data acquisition unit 62. By inputting the inference data acquired by the data acquisition unit 62 into the trained model, the inference unit 63 can output the disembarking route of the person from the inference data.

[0094] As another example, a trained model is stored in the trained model storage unit 61 for inferring the movement area of ​​a person in the cage 20C from inference data. The inference unit 63 uses the trained model stored in the trained model storage unit 61 to infer the movement area of ​​the person from the inference data acquired by the data acquisition unit 62. In this example, the inference unit 63 can output the movement area of ​​the person from the inference data by inputting the inference data acquired by the data acquisition unit 62 into the trained model.

[0095] As another example, the trained model storage unit 61 stores a trained model for inferring both the disembarking route and the travel area of ​​a person in the car 20C from inference data. The inference unit 63 uses the trained model stored in the trained model storage unit 61 to infer both the disembarking route and the travel area of ​​the person from the inference data acquired by the data acquisition unit 62. In this example, the inference unit 63 can output both the disembarking route and the travel area of ​​the person from the inference data by inputting the inference data acquired by the data acquisition unit 62 into the trained model.

[0096] As an example, the trained model is generated by the training device 7 described later. The trained model may also be a model generated by a device other than the training device 7. This device may include a server managed by the maintenance company that maintains the elevator 2, and a server managed by the management company of the mobile unit 3, etc.

[0097] Figure 7 is a flowchart showing an example of the operation of the inference device 6. The operation flow shown in Figure 7 corresponds to the process shown in S104 of Figure 2.

[0098] In the inference device 6, first, the data acquisition unit 62 acquires inference data (S501). Next, the inference unit 63 inputs the inference data acquired by the data acquisition unit 62 in S501 into the trained model stored in the trained model storage unit 61 (S502). Next, the inference unit 63 outputs the inference result obtained by inputting the inference data into the trained model in S502, that is, data indicating at least one of the disembarking route or passage area of ​​the subject in the car 20C (S503).

[0099] Next, the learning device 7 described above will be explained. Figure 8 shows an example of the learning device 7. The learning device 7 may be provided in the management device 5, or it may be provided in an external device that can communicate with the management device 5. The learning device 7 may also be provided in other devices other than the management device 5 and the said external device.

[0100] The learning device 7 learns at least one of the disembarking route or the passage area within the passenger's carriage 20C and generates the learned model. The learning device 7 may learn both the passenger's disembarking route and the passage area. The learning device 7 may learn only the passenger's disembarking route. The learning device 7 may learn only the passenger's passage area. The learning device 7 shown in Figure 8 comprises a data acquisition unit 71 and a model generation unit 72.

[0101] Training data is input to the learning device 7. The data acquisition unit 71 acquires the training data input to the learning device 7. The model generation unit 72 uses the training data acquired by the data acquisition unit 71 to generate a trained model for inferring at least one of the disembarking route or the travel area of ​​a person in the car 20C. As an example, the model generation unit 72 generates a trained model for inferring both the disembarking route and the travel area of ​​a person from the training data. The model generation unit 72 may also generate a trained model for inferring the disembarking route of a person from the training data. The model generation unit 72 may also generate a trained model for inferring the travel area of ​​a person from the training data.

[0102] As an example, the training data may include information indicating the destination floor F2 of the mobile unit 3A, information indicating the destination floor F3 of the user in the car 20C, and information indicating the positions of the mobile unit 3A and the user within the car 20C. The training data may also include information indicating the destination floor F2, information indicating the destination floor F3, and images taken inside the car 20C.

[0103] In addition to the information mentioned above, the training data also includes ground truth data. When generating a trained model to infer a person's disembarking route, the training data includes ground truth data indicating the person's disembarking route. When generating a trained model to infer a person's travel area, the training data includes ground truth data indicating the person's travel area. When generating a trained model to infer both a person's disembarking route and travel area, the training data includes ground truth data indicating both the person's disembarking route and travel area.

[0104] The inference data may also include information indicating the movement attributes of the user in cart 20C.

[0105] Furthermore, if the target is a user, a predictive model of the user's behavior patterns may be used as the ground truth data, i.e., the target's disembarking route, etc. If the target is a mobile object 3A, a predictive model of the movement of mobile object 3A may be used as the ground truth data. If the training data includes the user's movement attributes, a predictive model of behavior patterns corresponding to the user's movement attributes may be used as the ground truth data. These models are pre-configured.

[0106] The model generation unit 72 learns the correct data from training data created based on combinations of correct data and non-correct data.

[0107] As an example, data other than the correct answer data includes the destination floor F2 of the mobile vehicle 3A, the destination floor F3 of the user in the car 20C, and the positions of the mobile vehicle 3A and the user. The data other than the correct answer data may also include images taken inside the car 20C, as well as the destination floor F2 of the mobile vehicle 3A, the user's destination floor F3. The data other than the correct answer data may also include the movement attributes of the user in the car 20C.

[0108] For example, the model generation unit 72 learns the disembarking route of a subject from training data created based on combinations of data other than the ground truth data and the subject's disembarking route (ground truth data). In this example, the model generation unit 72 generates a trained model for inferring the subject's disembarking route from data other than the ground truth data, based on the training data acquired by the data acquisition unit 71.

[0109] As another example, the model generation unit 72 learns the target's travel area from training data created based on combinations of data other than the ground truth data and the target's travel area (ground truth data). In this example, the model generation unit 72 generates a trained model for inferring the target's travel area from data other than the ground truth data, based on the training data acquired by the data acquisition unit 71.

[0110] As another example, the model generation unit 72 learns the disembarking route and travel area of ​​a subject from training data created based on combinations of data other than the ground truth data and the subject's disembarking route and travel area (ground truth data). In this example, the model generation unit 72 generates a trained model for inferring both the disembarking route and travel area of ​​a subject from data other than the ground truth data, based on the training data acquired by the data acquisition unit 71.

[0111] As another example, the training data may include information from other combinations, and the model generation unit 72 may generate a trained model from that information to infer at least one of the subject's disembarking route or travel area.

[0112] Preferably, supervised learning is employed as the learning algorithm used by the model generation unit 72. If possible, known algorithms such as unsupervised learning or semi-supervised learning may be used as the learning algorithm. Deep learning, which learns to extract features themselves, may be used as the learning algorithm. Other known methods such as genetic programming, inductive logic programming, or support vector machines may be used as the learning algorithm.

[0113] As an example, let's explain how to apply a neural network.

[0114] The model generation unit 72 learns at least one of the subject's disembarking route or travel area through supervised learning according to a neural network model. Supervised learning is a method that learns features in training data by providing pairs of input and result (label) data to the learning device 7 and inferring results from the input.

[0115] A neural network consists of an input layer made up of multiple neurons, an intermediate layer (hidden layer) made up of multiple neurons, and an output layer made up of multiple neurons. The intermediate layer may be one layer or multiple layers. Figure 9 shows an example of a neural network applied to the learning device 7. Figure 9 shows an example of a three-layer neural network consisting of an input layer (X1-X3), an intermediate layer (Y1-Y2), and an output layer (Z1-Z3).

[0116] In the neural network shown in Figure 9, when multiple inputs are input to the input layer, their values ​​are multiplied by weight W1(w11-w16) and input to the hidden layer. The result is then multiplied again by weight W2(w21-w26) and output from the output layer. This output result varies depending on the values ​​of weights W1 and W2.

[0117] In the example shown in Figure 8, the neural network learns at least one of the subject's disembarking route or travel area through supervised learning based on training data acquired by the data acquisition unit 71. As described above, the training data is, for example, data created based on the destination floor F2 of the mobile vehicle 3A, the destination floor F3 of the user in the elevator car 20C, and the combination of the positions of the mobile vehicle 3A and the user with the subject's disembarking route (ground truth data). In this example, the neural network learns by inputting the destination floor F2 of the mobile vehicle 3A, the destination floor F3 of the user, and the positions of the mobile vehicle 3A and the user into the input layer and adjusting weights W1 and W2 so that the result output from the output layer is close to the subject's disembarking route (ground truth data).

[0118] The model generation unit 72 generates a trained model by performing the learning described above and outputs the generated trained model. The trained model output from the model generation unit 72 is stored in the trained model storage unit 61.

[0119] Figure 10 is a flowchart showing an example of the operation of the learning device 7. In the learning device 7, first, the data acquisition unit 71 acquires training data (S601). Next, the model generation unit 72 uses the training data acquired by the data acquisition unit 71 in S601 to learn, for example, the disembarking route or the area of ​​travel of the target person through supervised learning, and generates a trained model (S602). Next, the trained model generated by the model generation unit 72 is stored in the trained model storage unit 61 (S603).

[0120] As another example, some or all of the functions of the notification unit 33 described in this embodiment may be implemented by an information processing device 8 as shown in Figure 11. Some or all of the functions of the notification unit 57 may be implemented by an information processing device 8 as shown in Figure 11.

[0121] Figure 11 shows an example of an information processing device 8. When the management system 1 includes an information processing device 8, the information processing device 8 may be included in the mobile unit 3 or in the management device 5. The information processing device 8 may be provided as a separate device from the mobile unit 3 and the management device 5. For example, the information processing device 8 may be provided in a device that can communicate with the mobile unit 3. The information processing device 8 may be provided in a device that can communicate with the management device 5. Such a device may include a specific single server, a specific group of servers, a cloud server, etc.

[0122] If the management system 1 includes an information processing device 8, the management system 1 utilizes an artificial intelligence (AI) unit 9 to realize the desired function. As an example, the notification unit 33's function is realized by the information processing device 8 communicating with the artificial intelligence unit 9 in the management system 1. The notification unit 57's function may also be realized by the information processing device 8 communicating with the artificial intelligence unit 9. A preferred example of how the information processing device 8 realizes the function of the notification unit 33 will be described in detail below.

[0123] In this example, when input data is received, the information processing device 8 uses the artificial intelligence unit 9 to acquire and output output data including notification content N. The notification content N is the content for informing the passenger inside the elevator car 20C of at least one of the disembarking route or the passage area within the elevator car 20C. The information processing device 8 shown in Figure 11 comprises a data acquisition unit 81 and a control unit 82.

[0124] Input data is input to the information processing device 8. The data acquisition unit 81 acquires the input data input to the information processing device 8. The input data includes at least one of the disembarking route or the passage area within the passenger's carriage 20C. For example, the input data may include the passenger's disembarking route. The input data may also include the passenger's passage area. The input data may include both the passenger's disembarking route and passage area.

[0125] As another example, the input data may include information indicating the movement attributes of users in cart 20C. The input data may include information indicating the attributes of users in cart 20C. The input data may include information indicating the congestion status of cart 20C.

[0126] The control unit 82 functions as an interface that can exchange information with an external system. Input data is received by the control unit 82 from the data acquisition unit 81. The control unit 82 receives the input data acquired by the data acquisition unit 81 and inputs it to the artificial intelligence unit 9, thereby obtaining output data including the notification content N from the artificial intelligence unit 9. In other words, the control unit 82 inputs the input data acquired by the data acquisition unit 81 to the artificial intelligence unit 9 in order to obtain output data including the notification content N from the artificial intelligence unit 9.

[0127] The input data may include text data, image data, audio data, and video data. The input data may also include data in other formats. The output data may include control information written in a specific format that can be recognized by the control unit 32 of the mobile unit 3A. The output data may be, for example, source code written in a specific programming language.

[0128] The artificial intelligence unit 9 refers to artificial intelligence equipped with intelligent functions such as reasoning and judgment, and its operating environment. In this example, the artificial intelligence unit 9 is a model and its operating environment configured to output output data corresponding to input data when input data is received. The artificial intelligence unit 9 receives input data from the control unit 82 and outputs output data based on the input data and the trained model described later. The artificial intelligence unit 9 shown in Figure 11 includes a trained model storage unit 91 and a model control unit 92.

[0129] The trained model is stored in the trained model memory unit 91. The trained model includes model information, which will be described later. The trained model may also include model parameters, which are information that defines the behavior of the model, such as constraints, weighting variables, and evaluation functions.

[0130] Examples of models include Neural Networks (NN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Variational Autoencoders (VAE), Generative Adversarial Networks (GAN), Diffusion models, Transformers, Large Language Models (LLM), Visual Language Models (VLM), Bidirectional Encoder Representations from Transformers (BERT), Generative Pre-trained Transformers (GPT), and Contrastive Language Image Pre-training (CLIP). These models are not mutually exclusive. For example, LLM, VLM, BERT, and GPT can be included in the Transformer category. A Transformer can be included in the NN category.

[0131] A combination of multiple types of algorithms may be used as the learning algorithm. A combination of multiple types of models may be used as the model. A multimodal model, trained on a combination of multiple different types of data, may be used as the model.

[0132] When the model control unit 92 acquires input data, it outputs output data based on the input data and the trained model. That is, when the model control unit 92 acquires input data, it uses the trained model to generate output data corresponding to the input data and outputs it.

[0133] Furthermore, the trained model and other information used by the artificial intelligence unit 9 may be pre-prepared or acquired via the network as needed.

[0134] Figure 12 is a flowchart showing an example of the operation of the information processing device 8. In the information processing device 8, first, the data acquisition unit 81 acquires input data (S701). The data acquisition unit 81 outputs the acquired input data to the control unit 82. Next, the control unit 82 inputs the input data acquired by the data acquisition unit 81 to the artificial intelligence unit 9 (S702). Next, the control unit 82 acquires and outputs output data, which is the result obtained by inputting the input data to the artificial intelligence unit 9, i.e., the notification content N (S703). Then, the output data obtained from the artificial intelligence unit 9 in S703 is transmitted to the alarm device 30, etc.

[0135] Furthermore, if the input data includes either the passenger's disembarking route or the area they will be traveling through, the notification content N will be the content to inform the passenger of that route within the car 20C. If the input data includes both the passenger's disembarking route and the area they will be traveling through, the notification content N will be the content to inform the passenger of both routes within the car 20C.

[0136] Figure 13 shows an example of the hardware resources of the management device 5. The management device 5 includes a processing circuit 100 as a hardware resource, which includes a processor 101 and memory 102. The processing circuit 100 may include multiple processors 101. The processing circuit 100 may also include multiple memory 102.

[0137] In this embodiment, the parts indicated by reference numerals 50 to 57 represent functions of the management device 5. The function of the storage unit 50 is realized by the memory 102. The functions of the parts indicated by reference numerals 51 to 57 can be realized by software, firmware, or a combination of software and firmware written as a program. The program is stored in the memory 102. The management device 5 realizes the functions of the parts indicated by reference numerals 51 to 57 by executing the program stored in the memory 102 using the processor 101 (computer).

[0138] The processor 101 is also called a CPU (Central Processing Unit), central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, or DSP. The memory 102 may be a semiconductor memory, magnetic disk, flexible disk, optical disk, compact disk, minidisc, or DVD. Possible semiconductor memories include RAM, ROM, flash memory, EPROM, and EEPROM.

[0139] Figure 14 shows another example of the hardware resources of the management device 5. In the example shown in Figure 14, the management device 5 includes a processing circuit 100 that includes a processor 101, memory 102, and dedicated hardware 103. Figure 14 shows an example in which some of the functions of the management device 5 are realized by the dedicated hardware 103. All of the functions of the management device 5 may also be realized by the dedicated hardware 103. The dedicated hardware 103 can be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof.

[0140] The hardware resources of the inference device 6 are the same as those shown in the example in Figure 13 or Figure 14. The inference device 6 includes a processing circuit that includes a processor and memory as hardware resources. The processing circuit may include multiple processors. The processing circuit may also include multiple memories. The inference device 6 realizes the functions of each part shown by reference numerals 62 to 63 by executing a program stored in memory using a processor (computer). The inference device 6 may also include a processing circuit that includes a processor, memory, and dedicated hardware as hardware resources. Some or all of the functions of the inference device 6 may be realized by dedicated hardware.

[0141] The hardware resources of the learning device 7 are the same as those shown in the example in Figure 13 or Figure 14. The learning device 7 includes a processing circuit that includes a processor and memory as hardware resources. The processing circuit may include multiple processors. The processing circuit may also include multiple memories. The learning device 7 realizes the functions of each part shown by reference numerals 71 to 72 by executing a program stored in memory using a processor (computer). The learning device 7 may also include a processing circuit that includes a processor, memory, and dedicated hardware as hardware resources. Some or all of the functions of the learning device 7 may be realized by dedicated hardware.

[0142] The hardware resources of the information processing device 8 are the same as those shown in the example in Figure 13 or Figure 14. The information processing device 8 includes a processing circuit that includes a processor and memory as hardware resources. The processing circuit may include multiple processors. The processing circuit may also include multiple memories. The information processing device 8 realizes the functions of each part shown by reference numerals 81 to 82 by executing a program stored in memory using a processor (computer). The information processing device 8 may also include a processing circuit that includes a processor, memory, and dedicated hardware as hardware resources. Some or all of the functions of the information processing device 8 may be realized by dedicated hardware.

[0143] Examples of aspects that may be included in this disclosure are listed below as an addendum.

[0144] [Note 1] An elevator with a car, A mobile body that moves autonomously within the facility equipped with the aforementioned elevator, A management device capable of communicating with the elevator and the mobile body, A management system equipped with, Alarm and, A planning unit plans either the disembarking route or passage area for the person who will disembark first from the car, when at least one user is riding in the car on which the mobile vehicle is in and a destination floor different from the destination floor of the mobile vehicle is registered. A notification unit that notifies the aforementioned one, planned by the planning unit, from the notification device so that users other than the target person among those in the mobile vehicle and the cage can recognize it, A management system equipped with [features / equipment]. [Note 2] When the user in the aforementioned cage is the aforementioned target person, a route determination unit determines the movement path of the moving body within the cage so as not to obstruct the aforementioned one planned by the planning unit, A movement control unit moves the moving body along the movement path determined by the path determination unit, The management system described in Appendix 1, further equipped with the following features. [Note 3] The aforementioned alarm is capable of emitting light, The notification unit notifies the one planned by the planning unit by light from the notification device so that users other than the target person among the users in the mobile body and the cage can recognize it, as described in Appendix 1 or Appendix 2 of the management system. [Note 4] The aforementioned alarm is capable of emitting sound, The notification unit is a management system according to Appendix 1 or Appendix 2, wherein the notification unit notifies the one planned by the planning unit by sound from the notification device so that users other than the target person among the users in the mobile vehicle and the cage can recognize it. [Note 5] The planning unit plans the one described in any one of the appendices 1 to 4, based on the position of the moving body inside the cage and the position of the user in the cage. [Note 6] The planning unit plans the one described in any one of the appendices 1 to 4 based on images taken inside the cage. [Note 7] The planning unit plans the one described in Appendix 5 or Appendix 6 based on the movement attributes of the users in the basket. [Note 8] The planning department plans both the disembarking route and the passage area for the subject, The notification unit is a management system described in any one of Appendix 1 to Appendix 7, which notifies the notification unit of both of the above planned by the planning unit from the notification device. [Note 9] A control device capable of communicating with an elevator having a cage and a mobile body that autonomously moves within a facility equipped with the elevator, A planning unit plans either the disembarking route or passage area for the person who will disembark first from the car, when at least one user is riding in the car on which the mobile vehicle is in and a destination floor different from the destination floor of the mobile vehicle is registered. A communication unit transmits a notification to the mobile body so that the one planned by the planning unit can be recognized by the mobile body and by users in the car other than the target person, to inform the car. A management device equipped with this device. [Note 10] A control method for an elevator having a cage and a control device capable of communicating with a mobile body that autonomously moves within a facility equipped with the elevator, A planning step in which, when at least one user is in the car carrying the mobile vehicle and a destination floor different from the destination floor of the mobile vehicle is registered, plans either the disembarking route or the passage area of ​​the user who will get off the car the earliest among the users in the mobile vehicle and the car, A communication step of transmitting a notification to the mobile body so that the one planned in the planning step can be recognized by the mobile body and by users in the car other than the target person, to notify the car inside the car. A control method for a management device. [Note 11] A computer capable of communicating with an elevator having a cage and a mobile body that autonomously moves within a facility equipped with the elevator, When at least one user is in the car carrying the mobile vehicle and a destination floor different from the destination floor of the mobile vehicle is registered, a planning process is performed to plan either the disembarking route or the passage area of ​​the user who will get off the car the earliest among the users in the mobile vehicle and the car, Communication processing to transmit a notification to the mobile body so that the one planned in the planning process can be recognized by the mobile body and by users in the car other than the target person, within the car. A program to execute.

[0145] The items described in Appendix 2-8 may be added to each of the Appendix 9-11, similar to how they are added to Appendix 1. [Explanation of symbols]

[0146] 1 Management system, 2 Elevator, 3 Mobile unit, 4 Peripheral equipment, 5 Management device, 6 Inference device, 7 Learning device, 8 Information processing device, 9 Artificial intelligence unit, 20 Car, 21 Control device, 22 Alarm, 23 Weighing device, 24 Camera, 25 Door sensor, 30 Alarm, 31 Detector, 32 Control unit, 33 Notification unit, 34 Route determination unit, 35 Movement control unit, 40 Alarm, 41 Detector, 50 Memory unit, 51 First communication unit, 52 Second communication unit, 53 Third communication unit, 54 Processing unit, 55 Acquisition unit, 56 Planning unit, 57 Notification unit, 61 Trained model memory unit, 62 Data acquisition unit, 63 Inference unit, 71 Data acquisition unit, 72 Model generation unit, 81 Data acquisition unit, 82 Control unit, 91 Trained model storage unit, 92 Model control unit, 100 Processing circuit, 101 Processor, 102 Memory, 103 Dedicated hardware

Claims

1. An elevator with a car, A mobile body that moves autonomously within the facility equipped with the aforementioned elevator, A management device capable of communicating with the elevator and the mobile body, A management system equipped with, Alarm and, A planning unit plans either the disembarking route or passage area for the person who will disembark first from the car, when at least one user is riding in the car on which the mobile vehicle is in and a destination floor different from the destination floor of the mobile vehicle is registered. A notification unit that notifies the aforementioned one, planned by the planning unit, from the notification device so that users other than the target person among the users in the mobile vehicle and the cage can recognize it, A management system equipped with [features / equipment].

2. When the user in the aforementioned cage is the aforementioned target person, a route determination unit determines the movement path of the moving body within the cage so as not to obstruct the aforementioned one planned by the planning unit, A movement control unit moves the moving body along the movement path determined by the path determination unit, The management system according to claim 1, further comprising the above.

3. The aforementioned alarm is capable of emitting light, The management system according to claim 1 or 2, wherein the notification unit notifies the one planned by the planning unit by light from the notification device so that users other than the target person among the users in the mobile body and the cage can recognize it.

4. The aforementioned alarm is capable of emitting sound, The management system according to claim 1 or 2, wherein the notification unit notifies the one planned by the planning unit by sound from the notification device so that users other than the target person among the users in the mobile body and the cage can recognize it.

5. The management system according to claim 1, wherein the planning unit plans the one of the above based on the position of the moving body inside the cage and the position of the user in the cage.

6. The management system according to claim 1, wherein the planning unit plans the one based on an image taken inside the cage.

7. The management system according to claim 5 or 6, wherein the planning unit plans the one based on the movement attributes of the user in the basket.

8. The planning department plans both the disembarking route and the passage area for the subject, The management system according to claim 1 or 2, wherein the notification unit causes the notification device to notify both of the items planned by the planning unit.

9. A control device capable of communicating with an elevator having a cage and a mobile body that autonomously moves within a facility equipped with the elevator, A planning unit plans either the disembarking route or passage area for the person who will disembark first from the car, when at least one user is riding in the car on which the mobile vehicle is in and a destination floor different from the destination floor of the mobile vehicle is registered. A communication unit transmits a notification to the mobile body so that the one planned by the planning unit can be recognized by the mobile body and by users in the car other than the target person, to inform the car. A management device equipped with this device.

10. A control method for an elevator having a cage and a control device capable of communicating with a mobile body that autonomously moves within a facility equipped with the elevator, A planning step in which, when at least one user is in the car carrying the mobile vehicle and a destination floor different from the destination floor of the mobile vehicle is registered, plans either the disembarking route or the passage area of ​​the user who will get off the car the earliest among the users in the mobile vehicle and the car, A communication step of transmitting a notification to the mobile body so that the one planned in the planning step can be recognized by the mobile body and by users in the car other than the target person, to notify the car inside the car. A control method for a management device.

11. A computer capable of communicating with an elevator having a cage and a mobile body that autonomously moves within a facility equipped with the elevator, When at least one user is in the car carrying the mobile vehicle and a destination floor different from the destination floor of the mobile vehicle is registered, a planning process is performed to plan either the disembarking route or the passage area of ​​the user who will disembark from the car the earliest among the users in the mobile vehicle and the car, Communication processing to transmit a notification to the mobile body so that the one planned in the planning process can be recognized by the mobile body and by users in the car other than the target person, within the car. A program to execute.

12. A data acquisition unit that acquires data for inference, An inference unit that uses a trained model to infer either the disembarking route or the passage area of ​​a subject in an elevator car from the inference data, and outputs the one from the inference data acquired by the data acquisition unit, Equipped with, The aforementioned subject is the person who disembarks first from the elevator car when at least one user is riding in the elevator car carrying the autonomously moving vehicle within the facility equipped with the elevator, and a destination floor different from the destination floor of the vehicle is registered. The inference data includes, The destination floor of the aforementioned moving object, The destination floor of the passenger in the aforementioned cart, An image taken inside the aforementioned car, or the positions of the moving object and the user inside the aforementioned car, An inference device that includes this.

13. The inference device according to claim 12, wherein the inference data includes the movement attributes of the user in the basket.

14. A data acquisition unit that acquires training data, A model generation unit generates a trained model for inferring either the disembarking route or the passage area of ​​a subject in an elevator car, using the training data acquired by the data acquisition unit. Equipped with, The aforementioned subject is the person who disembarks first from the elevator car when at least one user is riding in the elevator car carrying the autonomously moving vehicle within the facility equipped with the elevator, and a destination floor different from the destination floor of the vehicle is registered. The aforementioned training data includes, The destination floor of the aforementioned moving object, The destination floor of the passenger in the aforementioned cart, An image taken inside the aforementioned car, or the positions of the moving object and the user inside the aforementioned car, The aforementioned one, It includes, The pre-trained model is a learning device that is a model for inferring one of the destination floors of the moving object and the destination floor of the user in the car, and the image or the position.

15. The learning device according to claim 14, wherein the learning data includes the movement attributes of the user in the basket.

16. A data acquisition unit that acquires input data, The control unit inputs the input data acquired by the data acquisition unit into the artificial intelligence, thereby acquiring and outputting output data. Equipped with, The aforementioned input data includes either the disembarking route or the area of ​​travel for the subject. The aforementioned subject is the person who gets off the elevator car first among the users in the elevator car and the mobile body that moves autonomously within the facility equipped with an elevator, when at least one user is in the elevator car and a destination floor different from the destination floor of the mobile body is registered. An information processing device in which the output data includes notification content for notifying the one in the cage.

17. The information processing apparatus according to claim 16, wherein the input data includes the movement attributes of the user in the basket.

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