JP7437279B2 - Elevator and elevator control method - Google Patents

Description

The present invention relates to an elevator and an elevator control method.

In an elevator system that controls multiple elevators, the number of people waiting in the elevator hall (floor) is measured and/or the number of people in the car is measured, and based on these measurement results, elevator assignments are made to improve operation efficiency. A technique for implementing this is known (Patent Document 1). In the technology described in Patent Document 1, the total number of people waiting is calculated from the number of people waiting in the elevator hall and the number of people in the car, and operation control is performed to allocate elevators.

Japanese Patent Application Publication No. 2013-124179

In the technology described in Patent Document 1 mentioned above, the number of people waiting in the elevator hall is measured, but this is a preliminary measurement result at any point in time until the arrival of the car, and it is different from the number of people getting on and off at the door opening when the car actually arrives. They may not match. If the number of people in the elevator hall is simply measured, the waiting time may be increased by the number of people getting off the car at the time of boarding and alighting, and there is a problem that the expected operating efficiency cannot be obtained. Furthermore, when the car is crowded, it is not possible to keep track of the number of people who get off the car and then get on and off again, so the number of passengers may differ from the actual number of passengers.

The present invention has been made in view of the above circumstances, and an object of the present invention is to reduce errors in measuring the number of people getting on and off an elevator.

In order to solve the above problems, an elevator according to one aspect of the present invention includes: a hall sensor that acquires the status of users in the hall as hall information; a car sensor that acquires the status of users in the car as car information; The elevator is equipped with an elevator that calculates the increase or decrease in the number of users at the landing or in the car when the car arrives at the landing based on the landing information acquired by the landing sensor and the car information acquired by the car sensor. A calculation unit is provided.

According to at least one aspect of the present invention, an increase or decrease in the number of users at the landing or in the car when the car arrives at the landing is calculated based on the landing information obtained by the landing sensor and the car information obtained by the car sensor. By performing the calculation, it is possible to reduce errors in measuring the number of people getting on and off the elevator. This makes it possible to improve the efficiency of elevator operation control.
Problems, configurations, and effects other than those described above will be made clear by the following description of the embodiments.

1 is a schematic configuration diagram showing an example of an elevator system according to a first embodiment of the present invention. FIG. 2 is a block diagram illustrating an example of the hardware configuration of a computer that constitutes each device included in the elevator system. FIG. 2 is a block diagram showing a configuration example of a car measuring section and a floor measuring section that calculate data equivalent to the number of people, according to a first example of the first embodiment of the present invention. FIG. 7 is a block diagram showing a configuration example of a car measuring section and a floor measuring section that calculate data equivalent to an occupied area according to a second example of the first embodiment of the present invention. It is a flowchart which shows the example of a procedure of calculation processing of the number of passengers getting on and off in the door open state according to the first embodiment of the present invention. FIG. 6A is a diagram showing an example of an elevator user before getting on and off, and FIG. 6B is a diagram showing an example of an elevator user after getting on and off. 12 is a flowchart illustrating an example of a procedure for estimating the number of people getting off the car before the arrival of the car according to the first example of the second embodiment of the present invention. It is a flowchart which shows the example of a procedure of the alighting area estimation process before the arrival of a car based on the 2nd example of the 2nd Embodiment of this invention. It is a diagram showing an example of a waiting area set on a floor. 12 is a flowchart illustrating an example of a procedure for re-boarding determination processing according to a third embodiment of the present invention. It is a figure showing an example of a user who gets off once and gets on again, and a user who does not get on again. It is a flow chart which shows the example of a procedure of door closing control concerning a 4th embodiment of the present invention. It is a flow chart which shows the example of a procedure of door opening control concerning a 5th embodiment of the present invention. It is a flowchart which shows the example of a procedure of the passenger spacing confirmation process based on the 6th Embodiment of this invention.

Hereinafter, examples of modes for carrying out the present invention will be described with reference to the accompanying drawings. In this specification and the accompanying drawings, components having substantially the same functions or configurations are given the same reference numerals and redundant explanations are omitted.

<First embodiment>
[Schematic configuration of elevator system]
First, a schematic configuration of an elevator system according to a first embodiment of the present invention will be described with reference to FIG. 1.
FIG. 1 is a schematic configuration diagram showing an example of an elevator system according to a first embodiment. The elevator system 100 shown in FIG. 1 is an elevator system that includes a car sensor installed on a car that moves up and down a hoistway, and a sensor installed on each floor.

A car sensor 10 is installed in the car 1. The car sensor 10 is arranged at a position where it can look down inside the car 1 from above and obtain information about the user's situation (car information). The car sensor 10 is connected to the car measuring section 30 via a communication path 12 (for example, a tail cord). The car measurement unit 30 performs measurement based on measurement data (car information) output by the car sensor 10.

The car 1 includes an input device such as a destination floor registration button for a user to register a destination floor, and an output device that outputs information such as the registered destination floor and the current position of the car 1. The input device and the output device may be configured by a touch panel device having a display function and a touch operation function. Further, the output device has a function (announcement function) of outputting audio from a speaker.

A floor sensor 20 is installed on the floor 2 (boarding hall). The floor sensor 20 is arranged at a position such as above the floor 2 where it can look down on the floor 2 and obtain information about the user's situation (hall information). For example, the floor sensor 20 is placed at a location around the landing door 92 where information about the user's situation can be obtained. The floor sensor 20 is connected to the floor measuring section 40 via a communication path 22. The floor measurement unit 40 (an example of a hall measurement unit) performs measurement based on measurement data (hall information) output by the floor sensor 20.

The elevator controller 50 (an example of an operation control unit) is a controller (an example of an operation control device) that controls a main engine (a motor of a hoisting machine) that is responsible for the operation of the car 1. Since the structure of the elevator system according to this embodiment is a well-known and commonly used structure, a description of the individual components of the elevator will be omitted.

The car 1 is provided with a car door 91 that is opened and closed by an opening and closing mechanism (not shown). Further, a landing door 92 is provided on the three-sided frame of the floor 2 and is disposed at a position facing the car door 91 when the car 1 is stopped on the floor 2. The car door 91 and the landing door 92 engage the car door 91 and the landing door 92 by the operation of the car door 91 when the car 1 lands on the floor 2, and this engagement reduces the driving force of the car door 91. is transmitted to the landing door 92, and the door lock means is configured to operate in response to the release of this engagement.

A door controller 90 that controls opening and closing of the car door 91 and the hall door 92 is connected to the communication path 70 via a communication path 93 . This allows the door controller 90 to communicate with the elevator controller 50 and group controller 80. The elevator controller 50 or the group controller 80 instructs the door controller 90 to open and close the car door 91 and the hall door 92 based on the calculation result of the state calculation unit 60.

The state calculation section 60 (an example of a calculation section) is connected to the car measurement section 30, the floor measurement section 40, the elevator controller 50, and the group controller 80 via a communication path 70. The state calculation section 60 calculates the number of people (users) in the car 1 and each floor 2 according to the elevator operation state controlled by the elevator controller 50 based on the measurement results of the car measurement section 30 and the measurement results of the floor measurement section 40. ) and the state of the object. The elevator operation status indicates a series of operation transitions in elevator operation, such as door closing, departure, acceleration, constant speed, deceleration, arrival, or door opening.

A group controller 80 in charge of operation control of a plurality of elevators (cars 1) is connected to the state calculation unit 60 via a communication path 70. The group controller 80 executes operation control such as elevator assignment based on the states of the people and objects calculated by the state calculation unit 60. In this embodiment, the efficiency and accuracy of elevator operation control are improved by being able to know in advance the availability of car 1, the number of people getting off from car 1, the number of people getting on from floor 2, and the number of people waiting on floor 2.

Note that FIG. 1 shows the configuration of one car 1 corresponding to one elevator and an arbitrary first floor (floor 2). Therefore, in the case of a building with multiple elevators and multiple floors, multiple car sensors 10 and multiple floor sensors 20 will be installed. Note that the floor sensor 20 only needs to be provided on at least one of the multiple floors (landing).

For the car sensor 10 and the floor sensor 20, an image sensor that outputs image data, a ToF (Time Of Flight) sensor or stereo camera that outputs distance image data, an RF (Radio Frequency) sensor that outputs point cloud data, etc. are used. However, the present invention is not limited thereto. When an RF sensor is used, the user's privacy can be protected. The state calculation unit 60 calculates state data such as individual positions, number of individuals, occupied area of individuals, and behavior of individuals and objects based on the output data of these sensors.

In this embodiment, each component is connected by communication paths 12, 22, 93, and 70, but the car sensor 10 and the car measuring section 30, and/or the floor sensor 20 and the floor measuring section 40 are The sensor may be integrated into one. Further, the state calculation unit 60 may be configured as a single sensor controller that integrates and processes a plurality of sensors, or may exist as an internal component of a group controller 80 that manages a plurality of elevators.

[Hardware configuration of each device]
Next, the hardware configuration of each device included in the elevator system 100 will be described with reference to FIG. 2. Here, the hardware configuration of the computers included in the car measurement section 30, floor measurement section 40, state calculation section 60, elevator controller 50, group controller 80, and door controller 90 will be described.

FIG. 2 is a block diagram showing an example of the hardware configuration of computers that constitute each device included in the elevator system 100. Computer C is an example of hardware used as a computer in this embodiment. Each block constituting the computer C is selected according to the function and purpose of use of each device. As the computer C, for example, a personal computer, a microcontroller, or the like can be used.

Computer C includes a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, a nonvolatile storage 106, and a communication interface 107, each connected to a system bus. The CPU 101, ROM 102, RAM 103, and nonvolatile storage 106 constitute a control unit.

CPU 101 reads software program codes that implement each function according to the present embodiment from ROM 102, loads them into RAM 103, and executes them. Variables, parameters, etc. generated during the calculation process of the CPU 101 are temporarily written to the RAM 103, and these variables, parameters, etc. are read out by the CPU 101 as appropriate. However, instead of the CPU 101, an MPU (Micro Processing Unit) may be used. The functions of the car measurement section 30, floor measurement section 40, state calculation section 60, elevator controller 50, group controller 80, and door controller 90 are realized by programs executed by the CPU 101.

As the nonvolatile storage 106, an HDD (Hard Disk Drive), an SSD (Solid State Drive), a disk device using magnetism or light, a nonvolatile semiconductor memory, or the like is used. In this non-volatile storage 106, in addition to an OS (Operating System) and various parameters, programs for making the computer C function are recorded. The ROM 102 and the non-volatile storage 106 record programs and data necessary for the operation of the CPU 101, and serve as an example of a computer-readable non-transitory storage medium that stores programs to be executed by the computer C. used. The learned networks 110, 111, 140, and 170 shown in FIGS. 3 and 4 are configured in the nonvolatile storage 106.

For example, a NIC (Network Interface Card) or the like is used as the communication interface 107, and various data can be sent and received between devices via a LAN (Local Area Network), dedicated line, etc. connected to the terminal of the NIC. It is possible.

Note that the display device 104 and the input device 105 may be connected to the computer C as shown by broken lines. The display device 104 is, for example, a liquid crystal display monitor, and displays the results of processing performed by the computer C. For example, a keyboard, a mouse, etc. are used as the input device 105, and the user can input predetermined operations and give instructions.

[Configuration of car measurement section and floor measurement section (number of people calculation)]
Next, as a first example in the first embodiment, the configurations of the car measuring section 30 and the floor measuring section 40 when calculating data equivalent to the number of people will be described with reference to FIG. 3.
FIG. 3 is a block diagram showing a configuration example of the car measuring section 30 and the floor measuring section 40 that calculate data equivalent to the number of people.

(image sensor)
When the car sensor 10 and the floor sensor 20 are image sensors, the general data that can be acquired by these sensors is image data. Calculating the number of people from image data can be achieved, for example, by using object recognition using artificial intelligence (AI). Machine learning based on deep learning using a neural network structure is often used in AI object recognition. In this case, the car measuring section 30 and the floor measuring section 40 are composed of an object inference section 120, a trained network (trained model) 110, and a person counting section 130. For example, in deep learning, convolutional neural networks are the most common trained network.

For example, when image data is input to the trained network 110, the trained network 110 extracts an image of a pixel area that matches the setting conditions (for example, an area corresponding to a circumscribed rectangle of the subject), and the image of that pixel area is Outputs a numerical value that represents the certainty that . The object inference unit 120 estimates that the image in the pixel region is a person when the numerical value output from the trained network 110 is equal to or greater than a predetermined value. The person counting unit 130 calculates and outputs the number of images of pixel regions estimated to be people by the object inference unit 120.

(ToF sensor/stereo camera)
When the car sensor 10 and the floor sensor 20 are ToF sensors/stereo cameras, the general data that can be acquired by these sensors is distance image data. The distance image data includes information representing the distance to the subject for each pixel. Calculating the number of people from distance image data can be achieved, for example, by utilizing segmentation using AI. Machine learning based on deep learning is often used for AI segmentation. In this case, the car measuring section 30 and the floor measuring section 40 are composed of a segment inference section 150, a learned network 140, and a segment counting section 160. With segmentation targeting people, the number of segments becomes the number of people.

For example, when distance image data is input to the trained network 140, the trained network 140 divides the distance image into multiple segments (for example, parts or regions corresponding to the outline of the subject) according to predetermined standards and rules, Outputs a numerical value that represents the certainty that the person is a person. The segment inference unit 150 estimates that the segment is a person when the numerical value output from the trained network 140 is equal to or greater than a predetermined value. The segment counting unit 160 calculates and outputs the number of segments estimated to be human by the segment inference unit 150.

(RF sensor)
When the car sensor 10 and the floor sensor 20 are RF sensors, the general data that can be acquired by these sensors is point cloud data indicating the position and radio wave reflection intensity. Calculating the number of people from point cloud data can be achieved, for example, by using machine learning clustering using statistical processing. For example, as a clustering method, there is DBSCAN (Density-based spatial clustering of applications with noise). In this case, the car measurement section 30 and the floor measurement section 40 are composed of a classification section 170 and a classification counting section 180. The number of instances determined by clustering is equivalent to the number of people.

For example, when point cloud data is input to the classification unit 170, the classification unit 170 groups the point cloud data based on predetermined criteria or rules, and classifies the data into instances of humans and other instances. The classification counting unit 180 calculates and outputs the number of instances classified as people by the classification unit 170 (number of classifications). Note that even when the car sensor 10 and the floor sensor 20 are RF sensors, AI (for example, machine learning using deep learning) may be applied to the car measurement unit 30 and the floor measurement unit 40, and a trained network may be used. In that case, point cloud data can be classified into people and objects with higher accuracy.

As described above, by utilizing various sensors such as an image sensor, a ToF sensor/stereo camera, and an RF sensor, it is possible to detect the number of users in the car 1 or on the floor 2. Further, as shown in FIGS. 7 and 8, which will be described later, it is also possible to obtain a motion vector based on the user's behavior from the difference in measurement results for each sensing cycle by each sensor.

As described above, the elevator (elevator system 100) according to the first embodiment has a hall measuring section (100) that measures the number of users in the hall (floor 2) from the hall information acquired by the hall sensor (floor sensor 20). It includes a floor measuring section 40) and a car measuring section that measures the number of users in the car from car information acquired by a car sensor. Then, the calculation unit (state calculation unit 60) calculates the number of people inside the landing or the car based on the measurement result of the number of users in the landing by the landing measurement unit and the measurement result of the number of users in the car by the car measurement unit. The system is configured to calculate an increase/decrease in the number of users as an increase/decrease in the number of users.

[Configuration of car measuring section and floor measuring section (occupied area calculation)]
Next, as a second example in the first embodiment, the configurations of the car measuring section 30 and the floor measuring section 40 when calculating data equivalent to the occupied area will be described with reference to FIG. 4.
FIG. 4 is a block diagram showing a configuration example of a car measuring section and a floor measuring section that calculate data equivalent to the occupied area.

(image sensor)
When the car sensor 10 and the floor sensor 20 are image sensors, detecting a human-equivalent area from the image data described above can be achieved by, for example, using object recognition that takes the area into account using AI (machine learning using deep learning, etc.). is possible. Mask R-CNN is an example of object recognition that takes regions into consideration. In this case, the car measuring section 30 and the floor measuring section 40 are composed of an object inference section 121, a trained network 111, and a human area calculation section 135. From a recognition result having a human-equivalent region, it is possible to obtain the occupied area of the human-equivalent region indicated by the recognition result. Note that in this specification, the occupied area may be an absolute value or a relative value representing the ratio of the area occupied by the user area to the area of the car 1 or the floor 2.

For example, when image data is input to the trained network 111, the trained network 110 extracts an image of a pixel region (e.g., a region corresponding to a subject) that matches the setting conditions considering the region, and the image of that pixel region is Outputs a numerical value that indicates the certainty that it is a person. The object inference unit 121 estimates that the image in the pixel region is a person when the numerical value output from the trained network 111 is equal to or greater than a predetermined value. The human area calculation unit 135 calculates and outputs the area of the image of the pixel area estimated to be a person by the object inference unit 121 (occupied area of the human equivalent area).

(ToF sensor/stereo camera)
When the car sensor 10 and the floor sensor 20 are ToF sensors/stereo cameras, detecting a human-equivalent area from the above-mentioned distance image data can be realized by, for example, using segmentation using AI (machine learning using deep learning, etc.). It is possible. In this case, the car measuring section 30 and the floor measuring section 40 are composed of a segment inference section 150, a trained network 140, and a segment area calculation section 165. It is possible to determine the occupied area of a region corresponding to a person from the area of the region segmented for humans.

For example, when distance image data is input to the trained network 140, the trained network 140 divides the distance image into multiple segments (for example, parts or regions corresponding to the outline of the subject) according to predetermined standards and rules, Outputs a numerical value that represents the certainty that the person is a person. The segment inference unit 150 estimates that the segment is a human-equivalent region when the numerical value output from the learned network 140 is greater than or equal to a predetermined value. The segment area calculation unit 165 calculates and outputs the area of the segment (person-equivalent region) estimated to be a person by the segment inference unit 150.

(RF sensor)
When the car sensor 10 and the floor sensor 20 are RF sensors, calculating the human-equivalent area from the above-mentioned point cloud data can be realized by, for example, utilizing clustering of machine learning using statistical processing. In this case, the car measurement section 30 and the floor measurement section 40 are composed of a classification section 170 and a classification area calculation section 185. It is possible to determine the occupied area of a human-equivalent region from the area of instances classified by clustering.

For example, when point cloud data is input to the classification unit 170, the classification unit 170 classifies the point cloud data into human and other instances based on predetermined criteria. The classification area calculation unit 185 calculates and outputs the area of the area occupied by the point cloud data corresponding to the instance classified as a person by the classification unit 170. Note that even when the car sensor 10 and the floor sensor 20 are RF sensors, AI (for example, machine learning using deep learning) may be applied to the car measurement unit 30 and the floor measurement unit 40, and a trained network may be used.

As described above, by utilizing various sensors such as an image sensor, a ToF sensor/stereo camera, and an RF sensor, it is possible to detect the area occupied by the user in the car 1 or on the floor 2. Further, as shown in FIGS. 7 and 8, which will be described later, it is also possible to obtain a motion vector based on the user's behavior from the difference in measurement results for each sensing cycle by each sensor.

As described above, the elevator (elevator system 100) according to the first embodiment includes a hall measurement unit that measures the area occupied by users of the hall (floor 2) from the hall information acquired by the hall sensor (floor sensor 20). (floor measurement unit 40); and a car measurement unit that measures the area occupied by the user in the car from the car information acquired by the car sensor. Then, the calculation unit (state calculation unit 60) calculates whether the landing area or It is configured to calculate an increase or decrease in the area occupied by the corresponding user as an increase or decrease in the number of users in the car.

[Procedure for calculating the number of passengers getting on and off]
Next, the procedure for calculating the number of passengers getting on and off when the operating state of the elevator system 100 is the door open state will be explained with reference to FIG.
FIG. 5 is a flowchart illustrating an example of a procedure for calculating the number of passengers getting on and off the vehicle when the door is open.

First, the state calculation unit 60 stores the state s0 of the user in the car 1 measured by the car measurement unit 30 from the car information immediately before the door opens, and stores the state s0 of the user in the car 1 measured by the floor measurement unit 40 from the hall information. The state s1 of the person is stored (S1).

Next, the state calculation unit 60 integrates information on the alighting state s2 of the car 1 from the measurement results of the users in the car 1 by the car measurement unit 30 (S2). The alighting state is a state in which an arbitrary person or object moves from the car 1 to the floor 2. That is, the information on the alighting state s2 is information on any person or object that alighted from the vehicle.

Further, in parallel with the processing in step S2, the condition calculation section 60 integrates information on the riding condition s3 on the floor 2 from the measurement results of the users on the floor 2 by the floor measurement section 40 (S3). The riding state is a state in which an arbitrary person or object moves from the floor 2 to the car 1. That is, the information on the riding state s3 is information on any person or object riding on the vehicle.

Next, the state calculation unit 60 obtains information on the current state s4 in the car 1 from the measurement results of the users in the car 1 by the car measurement unit 30 (S4). The number of users who have been on the train before is calculated using the formula [s4-s3]. This state s4 can be said to be a transient state before the end of getting off the vehicle.

Further, the state calculation unit 60 acquires information on the current state s5 of the floor 2 from the measurement results of the users on the floor 2 by the floor measurement unit 40 (S5). The number of users waiting on floor 2 is determined by the formula [s5-s2]. This state s5 can be said to be a transient state before the end of the ride.

Next, the status calculation unit 60 checks whether the user has finished getting off the car 1 (S6). If getting off the vehicle is not completed (NO in S6), the process returns to step S2, and if getting off the vehicle is completed (YES in S6), the process goes to step S8.

Next, the status calculation unit 60 checks whether the user has finished boarding the car 1 (S7). If the ride has not been completed (NO in S7), the process returns to step S3, and if the ride has been completed (YES in S7), the process proceeds to step S9.

Next, the state calculation unit 60 calculates the state s4 of the user of the car 1 after the user has exited the car using the formula [s0-s2+s3] (S8).

Further, the state calculation unit 60 calculates the state s5 of the user on the floor 2 after the ride is completed using the formula [s1+s2-s3] (S9).

In this manner, the state calculation unit 60 executes the above-mentioned process for calculating the number of passengers getting on and off, thereby making it possible to accurately calculate the number of passengers getting on and off while getting on and off. In FIG. 5 and FIGS. 6A and 6B, which will be described later, the number of users is measured as the status of users in car 1 and on floor 2, but the same effect can be obtained with a configuration that measures the area occupied by users. Of course, it can be done.

[Specific example of calculating the number of passengers]
The above-mentioned process of calculating the number of passengers getting on and off the vehicle will be specifically explained with reference to the example of the lifting and lowering operation shown in FIGS. 6A and 6B.
FIG. 6A shows an example of an elevator user before getting on and off, and FIG. 6B shows an example of an elevator user after getting on and off.

If the above-mentioned image sensor that outputs image data, ToF sensor/stereo camera that outputs distance image data, or RF sensor that outputs point cloud data is installed on the ceiling of car 1 and floor 2, the output result will be car 1. This is an image viewed from above of floor 2. Each sensor outputs various data corresponding to each human figure as shown in FIGS. 6A and 6B. In an image containing a human figure, the head and both shoulders of the person can be observed.

FIG. 6A shows the states of the users of car 1 and floor 2 before boarding and alighting. Nine people are in car 1, and 16 people are waiting on floor 2. FIG. 6B shows the states of the users of car 1 and floor 2 after getting on and off.

In Figures 6A and 6B, four people "1-2-3-4" get off from car 1, and seven people "A-B-C-D-E-F-G" get on from floor 2. There is. Therefore, the number of people in car 1 is 9-4+7=12, and the exact number of people waiting on floor 2 is 20-4-7=9. 20 is the total number of people involved in boarding and alighting, and is obtained by subtracting the number of people still in car 1 from the total number of people when the door is opened (16+9-5).

If measurements were only made without considering user behavior as in the past, the number of people waiting on floor 2 in FIG. 6B would be 16, the same as in FIG. 6A. The number of people continuing to ride in car 1 is 12-7=5. Since it can be confirmed that the number of people who will get off at the registered arrival floor after car 1 is at least five, it is possible to improve the efficiency of elevator allocation in the future. In addition, when a new destination floor is registered using the input device (destination floor registration button) of car 1, it can be confirmed that the number of new registrations is for a maximum of 7 people, improving the efficiency of future elevator allocation. It becomes possible to do so.

As described above, the elevator according to the first embodiment includes a hall sensor (floor sensor 20) that acquires the status of users at the hall (floor 2) as hall information, and a hall sensor (floor sensor 20) that acquires the status of users in the hall (floor 2) as car information. an elevator that is equipped with a car sensor that acquires information about the car at the landing or in the car when the car arrives at the landing based on the hall information acquired by the hall sensor and the car information acquired by the car sensor. It includes a calculation unit (state calculation unit 60) that calculates the increase or decrease in the number of users, and an operation control unit (elevator controller 50) that controls the operation of the elevator based on the calculation result of the increase or decrease in the number of users in the hall or in the car.

Further, in the elevator according to the first embodiment, the calculation unit (state calculation unit 60) determines whether to board the car based on the landing information and the car information when the operation status of the elevator is the door open state. After there are no more users, we calculate the increase or decrease in the number of users at the landing by reflecting the users who got off the car and the users who got on the car. The system is configured to calculate an increase or decrease in the number of users in the car by reflecting the users who have gotten off the car and the users who have boarded the car.

According to the first embodiment with the above configuration, based on the landing information obtained by the landing sensor and the car information obtained by the car sensor, the number of users at the landing or in the car when the car arrives at the landing is determined. By calculating the increase/decrease, it is possible to reduce measurement errors in the number of people getting on and off the elevator. This makes it possible to improve the efficiency of elevator operation control.

<Second embodiment>
As a second embodiment, a method of predicting the occurrence of alighting before the car 1 arrives at the destination floor will be described with reference to FIGS. 7 and 8.

[First example (processing for estimating the number of people getting off the train)]
First, as a first example of the second embodiment, a process for estimating the number of people getting off the car before arriving at the car will be described with reference to FIG.
FIG. 7 is a flowchart illustrating an example of a procedure for estimating the number of people getting off the car before arriving at the car. FIG. 7 shows a procedure for estimating the number of people getting off the elevator (car 1) when the elevator (car 1) is in a state where the elevator (car 1) is in the process of departing from an arbitrary floor and moving to the next floor.

For example, when an announcement of arrival at the next destination floor (floor) is made, or when deceleration is started to stop at the destination floor, in car 1, the user (including luggage) may be moved. Users who wish to get off at the next destination floor move toward the car door 91, and in response to this movement, users who do not want to get off at the destination floor move away from the car door 91. By using this user's movement (information on the direction of movement), it is possible to predict when the user will get off the vehicle. It is assumed that the car measurement unit 30 can acquire the position and motion vector of the measurement target (person or object).

First, the state calculation unit 60 obtains a motion vector group corresponding to the movement of the object to be measured from the difference in measurement results for each sensing cycle of the object to be measured in the car 1 by the car measurement unit 30 (S11).

Next, the state calculation unit 60 selects a motion vector corresponding to movement from the acquired motion vector group (S12). For example, motion vectors whose size is less than or equal to a predetermined value are excluded. As a result, minute vectors such as the shaking of the user's body can be eliminated, and movements such as walking can be extracted.

Next, the state calculation unit 60 classifies the motion vector group into motion vectors in a direction toward the car door 91 and motion vectors in a direction away from the car door 91 (S13).

Next, the state calculation unit 60 calculates the number of measurement objects indicated by the motion vector in the direction approaching the car door 91 (S14). The number of objects to be measured approaching the car door 91, that is, the number of users, is estimated to be the increase in the number of people who can board the car due to the users getting off the car when they arrive at the car.

As described above, the elevator according to the first example of the second embodiment includes a car measurement unit that measures the position of a user in the car from car information acquired by a car sensor, and a calculation unit (state calculation unit). Part 60) determines whether the car has arrived at the destination floor based on the difference in the measurement results for each sensing cycle of the users in the car in the car measurement unit, when the elevator is decelerating toward the destination floor or has not yet arrived. The system is configured to calculate the number of users estimated to get off the train later.

Conventionally, the number of people who can board the car has been determined based on the availability of the car. However, by executing the above-described process for estimating the number of people getting off the car, it is possible to predict the occurrence of vacancies in the car 1 due to getting off the car, that is, the increase in the number of people who can get on the car. By effectively utilizing the prediction results regarding the increase in the number of passengers who can board the elevator for operation control, it becomes possible to improve the operation efficiency of the elevator.

[Second example (alighting area estimation process)]
Next, as a second example of the second embodiment, an alighting area estimation process before the arrival of the car will be described with reference to FIG. 8.
FIG. 8 is a flowchart illustrating an example of a procedure for estimating the alighting area before the arrival of the car. FIG. 8 shows the procedure for estimating the area of the vacant area created by getting off the elevator (car 1) when the elevator (car 1) is in the process of leaving an arbitrary floor and moving to the next floor. .

Similar to the first example, when an announcement of arrival at the next destination floor (floor) is made or when deceleration is started to stop at the destination floor, the movement of the user including the luggage is stopped. By detecting this and using the direction of movement, it is possible to predict when the vehicle will get off the vehicle. It is assumed that the car measuring unit 30 can obtain the occupied area and motion vector of the object to be measured.

First, the state calculation unit 60 obtains a motion vector group corresponding to the movement of the measurement object from the difference in the measurement results for each sensing cycle of the measurement object in the car 1 by the car measurement unit 30 (S21).

Next, the state calculation unit 60 selects a motion vector corresponding to movement from the acquired motion vector group (S22). For example, as in FIG. 7, motion vectors whose magnitude is less than a predetermined value are excluded.

Next, the state calculation unit 60 classifies the motion vector group into motion vectors in a direction toward the car door 91 and motion vectors in a direction away from the car door 91 (S23).

Next, the state calculation unit 60 calculates the occupied area of the measurement target indicated by the motion vector in the direction approaching the car door 91 (S24). The occupied area of the object to be measured approaching the car door 91, that is, the occupied area of the user (including luggage), is estimated to be the increase in the boardable area caused by the user getting off the car upon arrival at the car.

As described above, the elevator according to the second example of the second embodiment includes a car measuring unit that measures the area occupied by the user in the car from the car information acquired by the car sensor, and a calculation unit (status When the operating state of the elevator is decelerating towards the destination floor or before arrival, the calculation unit 60) determines whether the car is on the destination floor based on the difference in the measurement results for each sensing cycle of the users in the car in the car measurement unit. The vehicle is configured to calculate the area occupied by the user who is estimated to get off the vehicle after arriving.

Conventionally, the number of people who can board the car has been determined based on the availability of the car. However, by executing the above-described alighting area estimation process, it is possible to predict the occurrence of vacancy in the car 1 due to alighting, that is, the increase in the boarding area. By effectively utilizing the prediction result regarding the increase in the rideable area for operation control, it becomes possible to improve the operation efficiency of the elevator.

As described above, in the elevator according to the second embodiment (first example, second example), the calculation unit (state calculation unit 60) calculates whether the operation status of the elevator is before reaching the destination floor. In addition, the system is configured to measure the behavior of the user in the car based on the car information from the car sensor, and to estimate from the measurement results that the user will get off the car after arriving at the destination floor.

<Third embodiment>
As a third embodiment, a method for determining whether a user who has once alighted from car 1 should re-board will be described with reference to FIGS. 9 to 11.

FIG. 9 shows an example of a waiting area set on a floor. If the car 1 is crowded, the passengers near the car door 91 will get off the car, and as shown in FIG. It stays at any position (area A3) from areas A1, A2) to behind the users "MN, OP" lined up on floor 2. Therefore, in this embodiment, a waiting area WA including areas A1 to A3 is set on the floor 2, and whether a passenger who has once gotten off the car 1 stays in the waiting area WA or not is determined whether or not to board the car again.

FIG. 10 is a flowchart illustrating an example of a procedure for re-boarding determination processing. FIG. 10 shows an example in which the number of passengers who get off the car 1 due to congestion etc., waits until the car 1 becomes available for boarding, and then measures the number of passengers who board the car 1 again.

First, the state calculation unit 60 measures the waiting area WA of users waiting on the floor 2 based on the measurement results of the users on the floor 2 by the floor measurement unit 40 (S31). Since the waiting area WA changes depending on the status of the users waiting on the floor 2, the waiting area WA is measured each time and stored in the RAM 103.

Next, the state calculation unit 60 checks whether there are any passengers getting off from the car 1 based on the measurement results of the users of the car 1 by the car measurement unit 30 (S32). If there are no passengers to get off the vehicle (NO in S32), the re-boarding determination process ends.

On the other hand, if there is a passenger getting off the vehicle (YES in S32), the state calculation unit 60 obtains the measurement results of the users on floor 2 by the floor measuring unit 40, and measures the behavior of the passenger who got off the vehicle (S33).

Next, the state calculation unit 60 determines whether the passenger who got off the vehicle remains within the waiting area WA (S34). Here, if the passenger who got off the train leaves the waiting area WA (NO in S34), the state calculation unit 60 counts the passenger as the number of people who get off the train and excludes him from the target of behavior measurement, that is, the number of people waiting ( S35).

On the other hand, if the passengers who alighted remain within the waiting area WA (YES in S34), the state calculation unit 60 counts the passengers as the number of people waiting (S36), and proceeds to step S33 to continue measuring the behavior. be subject to. The state calculation unit 60 appropriately executes the processes from step S33 to step S36 for all passengers who have alighted from car 1.

FIG. 11 shows examples of users who get off the train and then re-board, and users who do not re-board. FIG. 11 shows an example in which two people "1-2" out of the four people "1-2-3-4" who got off from car 1 in the state of FIG. 9 went out of the waiting area WA. There is. The two people "1-2" are judged to have completely disembarked and are excluded from the number of people waiting. Furthermore, the two people "3-4" who are near the landing door 92 after getting off the train are judged to have only temporarily gotten off the train, and are counted in the number of people waiting.

As described above, in the elevator according to the third embodiment, the calculation unit (state calculation unit 60) allows the user who gets off the car after the car arrives at the destination floor to ), the system is configured to include the user in the number of users waiting at the boarding point.

With this configuration, it is possible to re-identify a passenger who has gotten off the car from the car 1 as a person who is boarding from the floor 2, thereby increasing the accuracy of the number of users and improving the operating efficiency of the elevator.

<Fourth embodiment>
As shown in FIG. 1, the elevator system 100 includes a car sensor 10 provided inside the car 1, a floor sensor 20 provided on the floor 2 of each floor, and a door controller that controls the car door 91 and the hall door 92. 90. With this configuration, the measurement data of the car sensor 10, the measurement data of the floor sensor 20, and the measurement results around the car door 91 and the landing door 92 (operation vector, position data), the operations of the car door 91 and the landing door 92 can be controlled.

FIG. 12 is a flowchart illustrating a procedure example of door closing control according to the fourth embodiment. In FIG. 12, when the operating state of the elevator is a standby state until car 1 departs from an arbitrary floor (a state immediately before the door closes), the door Explain the procedure for controlling closing.

First, the state calculation unit 60 obtains a motion vector group corresponding to the movement of the object to be measured in the car 1 from the difference in the measurement results for each sensing cycle of the object to be measured in the car 1 by the car measurement unit 30 (S41 ).

Further, the state calculation unit 60 obtains a motion vector group corresponding to the movement of the measurement target on the floor 2 from the difference in the measurement results for each sensing cycle of the measurement target on the floor 2 by the floor measurement unit 40 (S42).

Next, from the motion vector group in the car 1 and on the floor 2, minute motion vectors unrelated to getting on and off the elevator, such as shaking of the user's body, are filtered (S43). This makes it possible to select motion vectors corresponding to movement from the motion vector group and extract motions such as walking of the user.

Next, the state calculation unit 60 determines whether the motion vector corresponds to getting on and off the elevator from the position and velocity of the motion vector extracted by filtering (S44). For example, if the motion vector is for car 1, it is determined that a motion vector that is not directed toward car door 91 is not equivalent to getting out of the car. Also, regarding the motion vectors on the floor 2, it can be determined that motion vectors that are not directed toward the hall door 92 are not suitable for boarding.

If there is a motion vector corresponding to getting on and off the elevator (S44: YES), the state calculation unit 60 outputs a command to the door controller 90 to keep the door open (S45). After the process in step S45, the process returns to step S41 and continues the series of processes.

On the other hand, if there is no motion vector corresponding to getting on and off the elevator (NO in S44), the state calculation unit 60 outputs a door closing command to the door controller 90. Upon receiving the door closing command, the door controller 90 closes the car door 91 and the hall door 92 (S46). After the process of step S46, the door closing control process ends.

As described above, in the elevator according to the fourth embodiment, the calculation unit (status calculation unit 60) calculates whether the operation status of the elevator is at the time of departure and the platform information is the situation where there are no users at the platform (floor 2) or when there are no users at the platform (floor 2). If the car corresponds to a situation where the car is not facing the door (landing door 92), and the car information corresponds to a situation where there are no users or a situation where the users in the car do not get off, each door of the landing and car is opened. It is configured to perform closing control.

With this configuration, conventionally the door was always kept open for a predetermined time even when there were no passengers getting on or off, but if the actions of the users of car 1 and floor 2 do not correspond to boarding or alighting, the door will remain open for a predetermined time. Doors can be closed ahead of time. Therefore, waiting time until departure can be shortened and operational efficiency can be improved.

<Fifth embodiment>
FIG. 13 is a flowchart illustrating an example of a door opening control procedure according to the fifth embodiment.
In FIG. 13, when the operating state of the elevator is such that the car 1 has arrived at an arbitrary floor (the state immediately before the door opens), the door opening is controlled based on the measurement results of the car sensor 10 and the floor sensor 20. Explain the steps to do so.

First, the state calculation unit 60 acquires a group of position data of the measurement object in the car 1 from the measurement results of the measurement object in the car 1 by the car measurement unit 30 (S51).

Further, the state calculation unit 60 obtains a position data group of the measurement target on the floor 2 from the measurement results of the measurement target on the floor 2 by the floor measurement unit 40 (S52).

Next, the state calculation unit 60 executes a process of extracting position data corresponding to the vicinity of the car door 91 or the landing door 92 from each of the obtained position data group of the car 1 and the position data group of the floor 2 ( S53).

Next, the state calculation unit 60 determines whether there is position data corresponding to the vicinity of the car door 91 or the landing door 92 (S54). Here, if there is no corresponding position data near the door (NO in S54), the door controller 90 executes the normal door opening of the car door 91 and the landing door 92 (S55). After this step S55 ends, the door opening control process ends.

On the other hand, if there is corresponding position data near the door (S54: YES), the state calculation unit 60 causes the door controller 90 to perform special door opening of the car door 91 and the landing door 92 (S56). For example, in special door opening, in order to make users who are leaning against the car door 91 or the landing door 92, or who are leaning near the door pocket, aware of the transition to the door opening situation, Open the door at a slower speed than when opening the door. After the process in step S56, the process returns to step S51 and continues the series of processes.

As described above, in the elevator according to the fifth embodiment, the calculation unit (status calculation unit 60) determines that when the operation status of the elevator is such that the landing information indicates that there is a user near the door of the landing (floor 2). The car is configured to control opening of the landing and each door of the car when there is no user near the door of the car and when the car information indicates that there is no user near the door of the car.

By doing this, conventionally the door is opened after a predetermined time has passed from the time of arrival, but based on the measurement results of the car sensor 10 and floor sensor 20, the situation around the door and three-sided frame can be confirmed. However, when there are no users near the landing door or car door, each door is opened. This can prevent the user's hands and arms from being drawn into the door pocket or the like. Additionally, if it is confirmed that the person is leaning against the door, door pocket, etc., a special door opening is performed and the door opening speed is made slower than normal door opening. Therefore, it becomes possible to provide safer operation control.

<Sixth embodiment>
FIG. 14 is a flowchart illustrating an example of a procedure for passenger spacing confirmation processing according to the sixth embodiment.
In FIG. 14, the procedure for measuring the distance between passengers in car 1 when the elevator is in the standby state, and maintaining the standby state if the distance between passengers is shorter than a predetermined distance will be explained. do.

First, the state calculation unit 60 checks whether there is a user in the car 1 based on the measurement results of the measurement target on the floor 2 by the floor measurement unit 40 (S61). If there is no passenger on board (NO in S61), the passenger interval confirmation process ends.

Next, if there is a user who has boarded the car (YES in S61), the status calculation unit 60 calculates a group of position data of the measurement target in the car 1 from the measurement results of the measurement target in the car 1 by the car measurement unit 30. (S62).

Next, the state calculation unit 60 generates a combination of position data from the acquired position data group (S63). Next, the state calculation unit 60 calculates the distance between the measurement objects (passengers) associated with the combined position data from the combined position data (S64).

Next, the state calculation unit 60 compares the calculated distance between the measurement objects with a predetermined value (S65), and determines whether the distance between the measurement objects is equal to or greater than the predetermined value (S66). If the distance between the measurement targets is equal to or greater than the predetermined value (S66: YES), the state calculation unit 60 determines whether all position data combinations have been compared with the predetermined value (S67). . If there remains a combination of position data that has not been subjected to the comparison process (NO in S67), the process returns to step S64, and calculations and comparisons are made on the intervals of the measurement objects for other combinations of position data.

On the other hand, if the state calculation unit 60 determines that all combinations of position data have been compared with the predetermined values (YES in S67), the elevator controller 50 transitions to a departure ready state (S68). For example, the car door 91 and the hall door 92 are closed by the door controller 90. After completing the process in step S68, the passenger spacing confirmation process ends.

Next, in step S66, if the state calculation unit 60 determines that the interval between any measurement targets is less than the predetermined value (NO in S66), the elevator controller 50 maintains the departure standby state (S69).

As shown in FIG. 1, the car 1 is equipped with an announcement function using an output device. The elevator controller 50 uses this announcement function to provide guidance to the effect that the distance between passengers cannot be met, and urges the passengers to move to a different location within the car 1 or get off the car.

As described above, in the elevator according to the sixth embodiment, the calculation unit (state calculation unit 60) compares the distance between users with a predetermined value based on car information before departure of the car, and If the distance between users is less than a predetermined value, the landing area (floor 2) and each door of the car will continue to be opened, and the output device in the car will notify that the distance between users is not maintained. If the distance between users is equal to or greater than a predetermined value, the landing and car doors are closed and the car enters a departure ready state.

According to the present embodiment with the above configuration, the main purpose of conventionally was to improve the filling efficiency of the car 1 based on the number of people and the occupied area and to control the operation in order to effectively utilize the space of the car 1. It is possible to perform operation control based on maintaining the interval between the two at a predetermined interval.

It should be noted that the present invention is not limited to the embodiments described above, and it goes without saying that various other applications and modifications can be made without departing from the gist of the present invention as described in the claims. . For example, each of the embodiments described above describes the configuration of the elevator system in detail and specifically in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to having all the components described. Moreover, it is possible to replace a part of the configuration of one embodiment with the component of another embodiment. It is also possible to add components of other embodiments to the configuration of one embodiment. Furthermore, it is also possible to add, replace, or delete other components to a part of the configuration of each embodiment.

Further, the present invention may have a configuration in which the car sensor 10 and the floor sensor 20 are combined into one sensor. For example, the car sensor 10 and the floor sensor 20 may be unified, and the floor sensor 20 may also serve as the car sensor 10. In this case, the floor sensor 20 is installed above the floor 2 (elevator hall) in a position where it can obtain information on users inside the car 1 and on the floor 2 when the car door 91 and the landing door 92 are opened. . The car sensor 10 can be deleted.

Further, each of the configurations, functions, processing units, etc. described above may be partially or entirely realized in hardware by designing, for example, an integrated circuit. As the hardware, a broadly defined processor device such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit) may be used.

In addition, in the flowcharts shown in FIGS. 5, 7, 8, 10, and 12 to 14, multiple processes may be executed in parallel or the processing order may be changed to the extent that the processing results are not affected. You can also

DESCRIPTION OF SYMBOLS 1... Car, 2... Floor, 3... Person, 10... Car sensor, 12... Car sensor communication path, 20... Floor sensor, 22... Floor sensor communication path, 30... Car measuring section, 40... Floor measuring section, 50... Elevator controller, 60... State calculation unit, 70... Communication path, 80... Group controller, 90... Door controller, 91... Car door, 92... Hallway door, 93... Communication path, 110, 111, 140... Learned network, 120 , 121... Object inference section, 130... Person counting section, 135... Person area calculation section, 150... Segment inference section, 160... Segment counting section, 165... Segment area calculation section, 170... Classification section, 180... Classification counting section, 185...Classification area calculation unit

Claims (11)

An elevator comprising a hall sensor that acquires the status of users in the hall as hall information, and a car sensor that acquires the status of users in the car as car information,
A calculation for calculating an increase or decrease in the number of users at the landing or in the car when the car arrives at the landing based on the landing information acquired by the landing sensor and the car information acquired by the car sensor. comprising a section ,
The calculation unit compares the distance between the users with a predetermined value based on the car information before the departure of the car, and if the distance between the users is less than the predetermined value, the calculation unit compares the distance between the users with a predetermined value. Continuing to open each door of the car, and notifying the output device in the car that the distance between the users is not ensured, and if the distance between the users is equal to or greater than a predetermined value, Close the doors of the landing area and the car and enter the state ready for departure.
elevator. When the operation state of the elevator is the door open state, the calculation unit calculates, from the landing information and the car information, the user who got off from the car and the user who got off the car after there were no more users boarding the car. The increase or decrease in the number of users at the platform is calculated by reflecting the number of users who have boarded the car, and further, after there are no users who get off from the car, the number of users who have gotten off from the car and the number of users who have boarded the car are calculated. The elevator according to claim 1, wherein an increase or decrease in the number of users in the car is calculated by reflecting the number of users. The calculation unit measures the behavior of the user in the car based on the car information of the car sensor when the elevator is in operation before reaching the destination floor, and determines the behavior of the user in the car based on the measurement result. The elevator according to claim 1, wherein it is estimated that the user will get off the elevator after arriving at the elevator. If the calculation unit determines that the user who got off the car after the car arrives at the destination floor remains within the set area of the landing area, the calculation unit The elevator according to claim 1, which is included in the number of people. a hall measurement unit that measures the number of users of the hall from the hall information acquired by the hall sensor;
a car measuring unit that measures the number of users in the car from the car information acquired by the car sensor,
The arithmetic unit calculates the number of users in the hall or in the car based on the measurement result of the number of users in the car by the hall measurement unit and the measurement result of the number of users in the car in the car measurement unit. The elevator according to any one of claims 1 to 4, wherein an increase or decrease in the number of users is calculated as an increase or decrease in the number of users. a landing measuring unit that measures an area occupied by users of the landing from the landing information acquired by the landing sensor;
a car measuring unit that measures the area occupied by the user in the car from the car information acquired by the car sensor;
The calculation unit calculates the area of the landing area or the car based on the measurement result of the area occupied by the users of the landing area in the landing measuring unit and the measurement result of the area occupied by the users in the car in the car measuring unit. The elevator according to any one of claims 1 to 4, wherein an increase or decrease in the area occupied by the corresponding user is calculated as an increase or decrease in the number of users within the elevator. a car measuring unit that measures the position of the user in the car from the car information acquired by the car sensor;
The calculation unit calculates whether the car is running from the difference between the measurement results for each sensing cycle of the users in the car in the car measurement unit when the elevator is in a state of deceleration heading toward the destination floor or before arriving at the destination floor. The elevator according to claim 3, wherein the number of users estimated to get off the elevator after arriving at the destination floor is calculated. a car measuring unit that measures the area occupied by the user in the car from the car information acquired by the car sensor;
The calculation unit calculates whether the car is running from the difference between the measurement results for each sensing cycle of the users in the car in the car measurement unit when the elevator is in a state of deceleration heading toward the destination floor or before arriving at the destination floor. The elevator according to claim 3, wherein an area occupied by a user estimated to get off the elevator after arriving at the destination floor is calculated. The calculation unit is configured to calculate that when the operating state of the elevator is at the time of departure and the platform information corresponds to a situation where there is no user at the platform or a situation where the user is not heading to the door, and the car information corresponds to The elevator according to claim 1, wherein the elevator is controlled to close the doors of the landing and the car when there are no users or when a user in the car does not get off the car. The calculation unit is configured to determine whether the elevator operation status is such that when the elevator reaches the destination floor, the landing information is in a situation where there are no users near the door of the landing, and the car information is in a situation where there are no users near the door of the car. In some cases, control is performed to open each door of the landing and the car, and the landing information indicates that there is a user near the door of the landing, or the car information indicates that there is a user near the door of the car. control to open each door of the landing and the car at a speed slower than a normal door opening speed when the situation is such that
The elevator according to claim 1 . A landing sensor that acquires the status of users in the elevator car as hall information, a car sensor that acquires the status of the users in the elevator car as car information, a calculation unit, and an operation control unit. An elevator control method using an elevator,
The calculation unit determines the number of users at the landing or in the car when the car arrives at the landing, based on the landing information acquired by the landing sensor and the car information acquired by the car sensor. Processing to calculate increase/decrease,
A process of controlling the operation of the elevator based on the calculated increase/decrease in the number of users at the landing or in the car by the operation control unit;
The calculation unit compares the distance between users with a predetermined value based on the car information before departure of the car, and if the distance between the users is less than the predetermined value, Continuing to open each door of the car, and notifying the output device in the car that the distance between the users is not ensured, and if the distance between the users is equal to or greater than a predetermined value, a process of closing each door of the landing area and the car to transition to a departure ready state;
An elevator control method including:

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