JP2024043985A - Car estimating device and car estimating method - Google Patents

Abstract

[Problem] To estimate the car in which a user is riding without requiring a dedicated device. [Solution] A car riding estimation device according to one embodiment includes a user data acquisition unit, a driving data acquisition unit, an estimation processing unit, and a data output unit. The user data acquisition unit acquires user data including a first time when a user passes a first floor in a building and a second time when the user passes a second floor different from the first floor. The driving data acquisition unit acquires driving data of a plurality of cars installed in the building. The estimation processing unit estimates the car in which the user is riding and the operating section among the plurality of cars based on the user data acquired from the user data acquisition unit and the driving data acquired from the driving data acquisition unit. The data output unit outputs the result estimated by the estimation processing unit in a predetermined data format. [Selected Figure] Figure 8

Description

Embodiments of the present invention relate to a car estimation device and a car estimation method.

In order to improve the service of moving within a building, there is a need for an elevator operation support service that enables data-driven simulations (digital trial runs) for preliminary verification of operation analysis etc. to be carried out using elevator operation data and people flow data. Therefore, it is necessary to understand the movement of users within the building.

Here, there is a method of estimating the departure floor and arrival floor of the user based on information such as the registration information of the hall call of each floor obtained from the elevator system, the parking floor of the car, and the loaded load. However, with this method, it is not possible to know which floors each user gets on and off, and when to get on and off.

JP 2004-137005 A JP 2019-81626 A

As mentioned above, the information obtained from the elevator system does not allow information such as which floor each user boards, when they board, or which car they board. There are also methods that use mathematical or statistical models or simulation models based on information obtained from the elevator system, but it is difficult to reflect differences between individual users and differences in trends between buildings. There are also methods that use cameras and beacon systems, but these require the installation of dedicated equipment, which incurs management and operation costs.

The problem to be solved by the present invention is to provide a car estimation device and a car estimation method that can estimate the car in which a user rides without requiring a dedicated device.

The car passenger estimation device according to one embodiment includes a user data acquisition unit, a driving data acquisition unit, an estimation processing unit, and a data output unit.

The user data acquisition unit includes a first time when the user passes through a first floor in the building and a second time when the user passes through a second floor different from the first floor. Obtain personal data. The operation data acquisition unit acquires operation data of a plurality of cars installed in the building. The estimation processing unit determines whether the user has boarded the car in each car based on the user data acquired from the user data acquisition unit and the driving data acquired from the driving data acquisition unit. Estimate the car and the operating section. The data output section outputs the result estimated by the estimation processing section in a predetermined data format.

FIG. 1 is a diagram showing the overall system configuration according to one embodiment. FIG. 2 is a diagram showing measurable information and information that requires estimation on the user's travel route. FIG. 3 is a diagram for explaining a method for estimating an elevator use time from a user's walking time. FIG. 4 is a diagram showing the elevator car running line. FIG. 5 is a diagram showing an example of calculation of the boarding probability and the alighting probability. FIG. 6 is a diagram for explaining a method of correcting the estimated walking time at the arrival floor. FIG. 7 is a diagram for explaining a method of correcting the estimated walking time of the user on the departure floor. FIG. 8 is a block diagram showing the configuration of the car estimation device in the same embodiment. FIG. 9 is a diagram showing an example of gate passage data obtained from the entrance/exit management system as user data used in the car estimation device. FIG. 10 is a diagram showing an example of elevator operation data used in the elevator car estimation device, which is obtained from a group management control device of the elevator car system. FIG. 11 is a diagram showing an example of the hardware configuration of the car estimation device. FIG. 12 is a flowchart showing the processing operation of the car estimation device.

Hereinafter, embodiments will be described with reference to the drawings.
Note that the disclosure is merely an example, and the invention is not limited to the content described in the embodiments below. Modifications that can be easily conceived by those skilled in the art are naturally included within the scope of the disclosure. In order to make the explanation more clear, in the drawings, the size, shape, etc. of each part may be changed from the actual embodiment and shown schematically. In some drawings, corresponding elements are designated by the same reference numerals, and detailed description thereof may be omitted.

Figure 1 is a diagram showing the overall configuration of a system according to one embodiment. In the figure, 100 indicates a building. This building 100 is equipped with an elevator system 110 and an entrance/exit management system 120.

The elevator system 110 controls a plurality of elevators (cars) installed in the building 100. Note that the number of elevators (cars) is arbitrary and is not limited to the example shown in FIG. The elevator system 110 includes control panels 112a, 112b, . . . , 112f corresponding to each elevator, and a group management control device 113. The control panels 112a, 112b...112f and the group management control device 113 each consist of a computer equipped with a CPU, ROM, RAM, etc.

The control panels 112a, 112b...112f control the operation of the cars 111a, 111b...111f under the control of the group management control device 113. Specifically, they control a motor (hoist) (not shown) for raising and lowering the cars, and control the opening and closing of the doors. The cars 111a, 111b...111f are provided in the elevator shaft, and move between floors in response to hall calls or car calls. A "hall call" is a call signal registered by operating a hall call button installed in the elevator hall of each floor, and includes information on the registered floor and destination direction. A "car call" is a call signal registered by operating a destination floor button installed in the car room, and includes information on the destination floor.

The group management control device 113 exists as a main control device and centrally controls the operation of the cars 111a, 111b, . . . 111f. The group management control device 113 acquires operation data of the cars 111a, 111b...111f through the control panels 112a, 112b...112f. These operating data include the running states of the cars 111a, 111b, . . . 111f, position information, loaded loads, door opening/closing states, call registration information, and the like. When a new hall call occurs, the group management control device 113 selects an assigned car from among the cars 111a, 111b...111f based on these operation data, and assigns the car to the floor where the hall call is registered. Perform processing such as responding to.

"Assigned car" refers to a car to which a hall call is assigned. Note that a commonly known method is used for assigning hall calls. In general, a method is used in which a specified evaluation function formula is used to find an evaluation value when a hall call is assigned to each car, and the car with the highest evaluation value is selected as the assigned car.

On the other hand, the entrance/exit management system 120 is composed of a computer equipped with a CPU, ROM, RAM, etc., and manages the entrance/exit of users. The entrance/exit management system 120 is connected to entrance/exit gates 121 and 124 provided on the entrance/exit floors of the building 100 and floor gates 122 and 123 provided on each floor. Each gate 121 to 124 has a function of authenticating users. The entrance/exit management system 120 manages whether a user can pass through each gate and records the time of passage. Note that security cards, biometric authentication, ID/passcodes, and the like are widely used as user authentication methods. In the present invention, any method may be used as long as it can identify the user and determine the passage between gates.

Here, for example, when the user P1 heads from the entrance/exit floor of the building 100 to his/her tenant located on an arbitrary floor, the user P1 takes the following travel route.
First, the user P1 walks to the elevator hall 101 through the entrance/exit gate (departure floor gate) 121 installed on the entrance floor. At this time, the passing time of the user P1 is recorded in the entrance/exit management system 120 together with the ID (identification information) of the user P1. The user P1 who has come to the elevator hall 101 registers an upward hall call by operating the hall call button 114 and waits for the arrival of the car. Note that if the entrance/exit gate 121 is equipped with a function of automatically registering a hall call along with authentication of the user P1, the hall call button 114 is not necessary.

Suppose now that the car 111f responds to the hall call registered by the user P1. The user P1 gets on the car 111f and registers the destination floor by operating a destination floor button (not shown). As a result, the car 111f moves toward the destination floor of the user P1. When the car 111f arrives at the destination floor, the user P1 gets off there and enters the tenant's occupied area from the elevator hall 103 through a floor gate (arrival floor gate) 122 installed in the common area of the floor. When the user P1 passes through the floor gate 122, the time of passage is recorded in the entrance/exit management system 120 together with the ID of the user P1.

In this embodiment, the car type estimation device 200 is connected to the elevator system 110 and the entrance/exit management system 120. The car type estimation device 200 acquires operation data for each car from the elevator system 110, acquires user data from the entrance/exit management system 120, and analyzes and processes this data to estimate the car in which the user is riding.

The car estimating device 200 consists of a computer equipped with a CPU, ROM, RAM, and the like. The car estimation device 200 may be installed within the building 100 or may be installed outside as a cloud server. Data exchange between the car estimating device 200 and each system 110, 120 may be carried out via a communication line built within the building 100 or the Internet, or may be carried out via the Internet and cloud typified by IoT. It may also be done through the system.

1, Ta to Te represent the time when user P1 passed each location, and t1 to t4 represent the time required for user P1 to move between each location.
Ta: departure floor gate passing time, Tb: hall arrival time, Tc: boarding time, Td: disembarking time, Te: arrival floor gate passing time, t1: walking time, t2: waiting time, t3: boarding time, t4: walking time

Further, P2 in the figure indicates another user. In the example shown in FIG. 1, user P2 walks from any floor through the floor gate (departure floor gate) 123 to the elevator hall 102, rides the car 111b to the entrance floor, and goes to the entrance/exit gate (arrival floor gate). The figure shows how the building exits through the floor gate) 124.

FIG. 2 is a diagram showing information that can be measured and information that requires estimation on the travel route of the user P1. The information shown in group D1 is gate passage information obtained from the entrance/exit management system 120, and is measurable information. The information shown in group D2 is elevator operation data obtained from the elevator system 110, and is measurable information. The information shown in group D3 includes walking time on the departure floor, waiting time, boarding time, walking time on the alighting floor, hall arrival time, boarding time, and alighting time, and is information that requires estimation.

Gate passage information (D1 group) of each user is obtained from the entrance/exit management system 120. From this gate passage information, OD (Origin-Destination) information regarding the departure floor and destination floor for each user can be extracted. However, information such as which car each user boarded cannot be obtained.

In the elevator system 110, except for a destination control system (DCS), it is difficult to determine the boarding car and boarding floor for each user. The operating data (D2 group) of the elevator system 110 includes information regarding the operating state of the car, but does not include information such as waiting time and boarding time. In other words, the access control system 120 and the elevator system 110 do not hold the information shown in group D3.

Below, we will explain a method for estimating the car (car) in which a user boards and information about group D3 using user data from the entrance/exit management system 120 and operation data from the elevator system 110. Note that we will use user P1 as an example, but in reality, a similar estimation process is repeatedly performed for multiple users on each floor.

Figure 3 is a diagram for explaining a method for estimating elevator use time from the walking time of user P1. In the figure, e1 is the estimated walking time, e2 is the estimated hall arrival time, e3 is the estimated disembarking time, and e4 is the estimated walking time.

First, to narrow down the cars that user P1 has boarded, the time e2 when user P1 arrives at the elevator hall 101 at the departure floor and the time e3 when user P1 gets off the car at the arrival floor are derived. For this purpose, an initial value of the estimated walking time e1 between the entrance/exit gate (departure floor gate) 121 and the elevator hall 101, and an initial value of the estimated walking time e4 between the elevator hall 103 at the arrival floor and the floor gate (arrival floor gate) 122 are set. These initial values are set, for example, from the distance between the gate and the elevator hall and the average walking speed of users. Alternatively, they are set from the results of actually measuring the walking time on-site.

Here, since the gate passing time Ta of user P1 at the departure floor and the gate passing time Te of user P1 at the arrival floor are known, the estimated hall arrival time e2 and estimated disembarking time e3 are calculated based on these times. The estimated hall arrival time e2 is an estimate of the time when user P1 arrives at the elevator hall 101 of the departure floor, and is obtained by adding the estimated walking time e1 to the gate passing time Ta (e2 = Ta + e1). The estimated disembarking time e3 is an estimate of the time when user P1 disembarks at the elevator hall 103 of the arrival floor, and is obtained by subtracting the estimated walking time e4 from the gate passing time Te (e3 = Te - e4).

Fig. 4 is a diagram showing elevator car operation lines. The horizontal axis indicates time, and the vertical axis indicates the floors at which the car stops. In this example, the operation status of four elevator cars is shown.
A section where the elevator car reverses its operating direction is defined as an "elevator operating section." The section indicated by 401 in the figure is an example of an "elevator operating section." For example, if an elevator car reverses its operating direction to the up direction on the third floor, stops on the twelfth floor, continues to operate in the up direction, and then reverses its operating direction to the down direction on the fourteenth floor, the third floor is the start point of the operating section and the fourteenth floor is the end point of the operating section. Passengers getting on and off are determined at each section of the operating section.

As a basic concept, a car that the user P1 can board satisfies the following conditions.
- The car is a car that stopped on the user's departure floor after the estimated hall arrival time e2 of the user P1, and the driving direction of the car matches the direction of the user's destination.
- On the arrival floor of the user, the estimated alighting time e3 of the user P1 is included within the time the car stops in the elevator hall.
In the example of FIG. 4, the car having the operating section 402 can be inferred as the car of the user P1. Actually, a car that meets the above conditions is searched for each user from all the operation sections of the cars.

Here, when multiple elevators have similar operation schedules, it may be difficult to narrow down the elevator to one that meets the above conditions. In this case, it is necessary to select the most accurate solution from among multiple solutions. The estimated hall arrival time e2 and the estimated disembarking time e3 are estimated values calculated based on the average walking time of each user between the departure floor and the arrival floor, and when expressed by a normal distribution model centered on the average value, each has a certain time span. Taking this time span into consideration, the number of elevator candidates increases. Therefore, by utilizing the fact that the estimated hall arrival time e2 and the estimated disembarking time e3 have a distribution, the boarding probability and disembarking probability are calculated, and the product of these is defined as the boarding and disembarking probability.
Probability of getting on and off = Probability of getting on × Probability of getting off

FIG. 5 is a diagram showing an example of calculation of the boarding probability and the alighting probability.
The operation diagram 500 corresponds to one trip of a certain car extracted from the operation diagram shown in FIG. 4. The operating state of the car transitions with the events of "stop", "door open", "door close", and "departure", indicated by a, b, c, and d in the diagram. The "stop" event a causes the car to stop. The "door open" event b causes the door to be in a completely open state. The "door close" event c causes the door to start to close. The "departure" event d causes the car to start moving. It is considered that user P1 can get on and off the car between the "door open" and "door close" events, i.e., when the door is completely open.

On the departure floor, the constraint condition for the user P1 to board the car is that the user P1 must arrive at the elevator hall before the car departs, that is, before the door closes. Note that if user P1 has arrived before the door opens, the user waits until the door opens.

Here, the estimated hall arrival time e2 of the user P1 has a distribution proportional to the estimated walking time e1 on the departure floor. 501 in the figure is an arrival time distribution representing the time width of the estimated hall arrival time e2 of the user P1. d1 indicates the departure floor door opening time, and d2 indicates the departure floor door closing time. The boarding probability is calculated as the relationship between the arrival time distribution 501 and the door closing time d2, that is, the integral value (area of the distribution) until each car starts closing its door at the departure floor.

On the arrival floor, the constraint that allows the user P1 to get off the car is a section where the door is open. 502 in the figure is an alighting time distribution representing the time width of the estimated alighting time e3 of the user P1. d3 indicates the arrival floor door opening time, and d4 indicates the arrival floor door closing time. The alighting probability is calculated as the relationship between the alighting time distribution 502 and the door opening time d3, that is, the integral value (area of the distribution) of the section in which each car has its door open on the arrival floor. The boarding and alighting probabilities are calculated for the operating sections of all the cars, and the car that has the operating section where the boarding and alighting probability has the maximum value is estimated as the boarding car.

In addition, in the example of FIG. 5, the arrival time distribution 501 is a normal distribution model, but it is based on the statistical results of walking time for the required section (between entrance gate 121 and elevator hall 101) on the departure floor for each multiple users. Other distribution models created from the above may also be used. The same applies to the alighting time distribution 502, and even if other distribution models are created from the results of statistics on the walking time of the required section (between the elevator hall 103 and the floor gate 122) on the arrival floor for each plurality of users. good. In addition, although the explanation has been given using user P1 as an example, in reality, by calculating the boarding and alighting probability in the same manner as above for all the cars for each user on each floor, each user's The car each person boarded is estimated.

FIG. 6 is a diagram for explaining a method of correcting the estimated walking time at the arrival floor.
By estimating the boarding car for each user, it becomes possible to associate the movement of each user with the elevator operation data. In other words, when the boarding car of user P1 can be estimated, the boarding time Tc of user P1 at the departure floor can be regarded as the door opening time d1 of the boarding car (Tc = d1). Similarly, the disembarking time Td of user P1 at the arrival floor can be regarded as the door opening time d3 of the boarding car (Td = d3). This makes it possible to obtain an estimate of the boarding and disembarking times of user P1 based on the elevator operation data (actual measurement data).

Here, walking time t4 can be estimated from the difference between gate passing time Te and door opening time d3 at the arrival floor (t4 = Te - d3). The initial estimated walking time e4 was set as an initial value based on walking distance and walking speed, etc. For this reason, it deviated from the actual walking time t4, and this deviation could have led to an error in determining which car to board. By receiving the estimation result of the car for user P1 and using the driving data of that car, it is possible to correctly estimate walking time t4 from when user P1 gets off the car to when he moves to the floor gate 122. The same is true for other floors, and by using the driving data of the car obtained as an estimation result, it is possible to correctly estimate the walking time from when the user gets off the car to when he moves to the gate.

FIG. 7 is a diagram for explaining a method of correcting the estimated walking time of the user on the departure floor.
Assuming that the walking time from the elevator hall to the gate is almost the same as the walking time from the gate on the same floor to the elevator hall, the statistical value of the walking time t4 at the time of getting off is calculated by comparing the statistical value of the walking time t4 when the user gets on the same floor It can be used as a statistical value of walking time when coming from a certain direction.

In other words, as shown in FIG. 7, the walking time t1 taken by user P1 to move from the entrance/exit gate 121 to the elevator hall 101 can be considered to be the same as the walking time taken by other users who got off at the same floor to move from the elevator hall 101 to the entrance/exit gate 121. This allows the estimated walking time e1 at the departure floor to be corrected to match the actual walking time t1.

Furthermore, the hall arrival time Tb is derived from the walking time t1, and the waiting time t2 is also derived from the difference between the boarding time Tc and the hall arrival time Tb. The boarding time t3 is obtained from the boarding time Tc and the alighting time Td. As a result, all of the information on the D3 group shown in FIG. 2 has been obtained.

The estimated walking times e1 and e4 are calculated by taking statistics on the walking times of users for each floor, for example, to calculate the average walking time and distribution (variance). In addition, if there are gates installed in multiple locations on each floor, and walking times vary depending on the route between the gates and the hall, walking time statistics may be calculated for each gate.

In addition, for example, in the case of an office on any floor, multiple users repeat the same departure and alighting floors, so it would be useful to calculate and use the statistical value of the walking time between the elevator hall and the gate for each user. good. By reflecting the statistical value of the walking time in the correction of the estimated walking times e1 and e4, it is possible to improve the accuracy of estimating the car.

FIG. 8 is a block diagram showing the configuration of the car estimation device.
The car passenger estimation device 200 includes a user data acquisition unit 801 for acquiring user data 810, and an operation data acquisition unit 803 for acquiring elevator operation data 820. The data may be acquired in either a form of receiving data transmitted from an external source, or a form of requesting and receiving data from an external source.

The user data 810 is data unique to each user, and includes at least identification information of the user, time data generated as appropriate as the user moves, and the like. Specifically, the user data 810 is gate passage data obtained from the entrance/exit management system 120 shown in FIG. 1 (see FIG. 9). In this case, the passenger car estimation device 200 is provided with a user data aggregation/conversion unit 802, which aggregates passage data obtained from a large number of gates, and calculates the passage time of the departure floor gate and the passage of the arrival floor gate for each user. It is necessary to convert the data into a data format that can be used for estimation processing, such as creating data classified by time. If the user data 810 has been processed into a data format that can be used for estimation processing, the user data aggregation/conversion unit 802 is not necessary.

The elevator operation data 820 is data related to the operation of the elevator, and includes at least car identification information, car position, door opening/closing information, and the like. Specifically, the operation data 820 is information related to the operation of a plurality of cars obtained from the group management control device 113 shown in FIG. 1 (see FIG. 10). In this case, if it is necessary to convert the driving data 820 into a format that can be used for estimation processing, such as when the format of the driving data 820 differs depending on the model, it is necessary to provide the driving data converter 804 in the car estimation device 200. There is. If data conversion is not required, the operation data conversion unit 804 is not necessary.

The estimation processing unit 805 estimates the car in which the user rides and the operating section of each car based on the user data and the operation data of the elevator. Specifically, the estimation processing unit 805 estimates the time at which the user arrives at the elevator hall on the first floor based on the first time when the user passes through the first floor (departure floor). Accordingly, the boarding probability indicating the probability that the user boarded the car from the first floor is calculated for each car. Furthermore, the estimation processing unit 805 estimates the time at which the user gets off at the second floor based on the second time at which the user passes the second floor (arrival floor). The alighting probability indicating the probability that the user alights on the second floor is calculated for each car. The estimation processing unit 805 estimates, as the car in which the user boarded, the car that has the operating section where the probability of getting on and off, which is obtained by multiplying the probability of getting on and getting off by multiplying the probability of getting on and off, is the maximum among each car.

The car passenger estimation device 200 may be provided with a calculation processing unit 806 for calculating the waiting time and number of people waiting for each floor based on the estimation results of the estimation processing unit 805. The waiting time can be calculated from the difference between the time when the user arrives at the elevator hall and the time when the user boards the car. The number of people waiting can be obtained by tallying up the waiting time for each user in chronological order.

The data output from the car estimation processing section 805 and the arithmetic processing section 806 is converted into a predetermined data format by the output conversion processing section 807 as needed, and is outputted as output data 830 through the data output section 808. This output data 830 includes the boarding car for each user, the waiting time for each floor, the number of people waiting, etc. Further, each time on the user's travel route obtained during the estimation process (hall arrival time, boarding time, alighting time, etc.) may be output together with the car estimation result.

Figure 9 shows an example of gate passage data obtained from the entrance/exit management system 120 as user data 810. Event information for each gate passage includes the occurrence time (time stamp), user ID, passed gate ID, and passage direction information. Note that the data items shown here are the minimum necessary, and other items may also be included.

FIG. 10 shows an example of the operation data of each car obtained from the group management control device 113 of the elevator system 110 as the elevator operation data 820. The operation data includes occurrence time (time stamp), car ID, event name, event attribute information, etc. Note that the data items illustrated here are the minimum necessary, and other items may be included.

(Hardware configuration)
FIG. 11 is a diagram illustrating an example of a hardware configuration of the car estimation device 200.
The car estimation device 200 includes, as hardware components, a CPU 11, a non-volatile memory 12, a main memory 13, a communication device 14, and the like.

The CPU 11 is a hardware processor that controls the operation of the car load estimation device 200. The CPU 11 executes various programs loaded from the non-volatile memory 12, which is a storage device, to the main memory 13. The programs executed by the CPU 11 include an operating system (OS) as well as a program 13a (hereinafter referred to as the car load estimation program) for executing the processing operations shown in the flowchart of FIG. 12.

The estimation process by the car estimation device 200 shown in FIG. 8 is realized by causing the CPU 11, which is a computer, to execute the car estimation program 13a. This car estimation program 13a may be stored in a computer readable recording medium and distributed, or may be downloaded to another computer via a network. Note that some or all of the functions of the car estimation device 200 may be realized by hardware such as an IC (Integrated Circuit), or may be realized as a combination of the software and hardware.

The non-volatile memory 12 and the main memory 13 are provided in the car load estimation device 200 and store various information including user data 810, elevator operation data 820, the car load estimation program 13a, etc. The communication device 14 is provided in the car load estimation device 200 and is configured to communicate with external devices via wired or wireless communication.

Next, the operation of this embodiment will be explained.
FIG. 12 is a flowchart showing the processing operation of the car estimation device 200. The process shown in this flowchart is executed by the car estimation device 200, which is a computer, reading the car estimation program 13a.

In the building 100 shown in FIG. 1, when a user uses an elevator to move from the first floor (departure floor) to the second floor (arrival floor), the car identification device 200 (car identification processing unit 805) estimates the car (car identification) that the user boarded and determines the operating section of that car by the following process. The process shown here is executed for each user to be analyzed.

In the following, in order to simplify the explanation, the explanation will be focused on the user P1 in conjunction with FIGS. 1 to 7.
First, the car estimation processing unit 805 sets initial values of the estimated walking time e1 of the user P1 on the departure floor and the estimated walking time e4 of the user P1 on the arrival floor (step S10). The initial values of the estimated walking times e1, e4 are set based on the distance between the gate and the elevator hall, the average walking speed of a typical user, etc., and have an error from the actual walking times t1, t4.

The car-type estimation processing unit 805 repeats the following optimal solution search processing loop until the car type determination converges (steps S11-S23). This optimal solution search processing loop is a processing loop for searching for a car type, and includes a processing loop for searching a travel route for each user to be analyzed (steps S12-S21) and a processing loop for searching an operating section for each car (steps S14-S19).

The boarding car estimation processing unit 805 uses the information on the estimated walking times e1 and e4 to calculate the estimated hall arrival time e2 and the estimated disembarking time e3 of user P1 (step S13). In detail, the boarding car estimation processing unit 805 adds the estimated walking time e1 to the gate passing time Ta of the departure floor obtained as the user data 810 to calculate the estimated hall arrival time e2. The boarding car estimation processing unit 805 also subtracts the estimated walking time e4 from the gate passing time Te of the arrival floor obtained as the user data 810 to calculate the estimated disembarking time e3. This state corresponds to FIG. 3.

Next, the car estimation processing unit 805 searches for a car that has an operating section where the probability of boarding and alighting the user P1 is the maximum value, as described below.
First, the car estimation processing unit 805 initializes the maximum value P_max of the getting on/off probability to 0 (step S15). The car estimation processing unit 805 calculates the probability of boarding and alighting of the user P1 for each car based on the elevator operation data 820 (step S16). Specifically, the estimation processing unit 805 compares the hall arrival time e2 and the estimated alighting time e3 with the operation process of each car obtained as the elevator operation data 820, and determines whether the user P1 is on the departure floor for each car. The probability that the user P1 can get on the train (boarding probability) and the probability that the user P1 can get off at the arrival floor (getting off probability) are calculated, and the product of these is calculated as the boarding and alighting probability.

If the boarding/alighting probability calculated in step S16 is greater than the boarding/alighting probability calculated up to that point, the estimation processing unit 805 updates the maximum value P_max (steps S17-S18). The estimation processing unit 805 calculates the boarding/alighting probability for the operating sections of all cars, and finally estimates the car having the operating section where the boarding/alighting probability is the maximum value P_max as the car for user P1, and determines its operating section (step S20). This state corresponds to Figure 4-5.

When the car of user P1 is estimated in this way, the estimation processing unit 805 corrects the estimated walking times e1 and e4 to approach the actual walking times t1 and t4 based on the operating section of the car (step S22). In detail, the estimation processing unit 805 estimates the walking time t4 from the difference between the gate passing time Te at the arrival floor and the door opening time d3, and corrects the estimated walking time e4 to approach the walking time t4. In addition, the estimation processing unit 805 regards the walking time t1 when user P1 moves from the entrance/exit gate 121 to the elevator hall 101 as the walking time when other users who got off at the same floor move from the elevator hall 101 to the entrance/exit gate 121, and corrects the estimated walking time e1 to approach the walking time t1. This state corresponds to Figure 6-7.

In this way, the process of estimating the car and operation section in which each user boards is repeated while correcting the estimated walking time between the departure and arrival floors for each user, and finally ends when the determination result of the car in which each user boards and the change in walking time fall below a preset threshold (i.e., when the determination result converges).

The car estimation result obtained by the estimation processing unit 805 is converted into a predetermined format and output to the outside. Further, as shown in FIG. 8, if the car estimating device 200 is equipped with the arithmetic processing unit 806, the waiting time and the number of people waiting on each floor are calculated based on the estimation results of the car, and together with the estimation results, It is converted into a predetermined format and output to the outside. The outside includes, for example, the elevator system 110.

In this way, according to this embodiment, by combining the user passage information for each floor managed by the building's entrance/exit management system with the elevator operation data held by the elevator system, it is possible to estimate the car in which the user boarded and its operating section without the need for dedicated equipment such as a camera.Furthermore, from the estimation results, information such as the number of people waiting on each floor and the waiting time can be obtained.

If these estimated results are fed into an elevator system, for example, it is possible to efficiently control the operation of each car, taking into account the traffic demand on each floor, and improve group management efficiency. Normally, on floors with many users, the allocation evaluation of cars for hall calls on that floor is strengthened, and the allocation evaluation of cars for hall calls on other floors is weakened. By knowing the number of people waiting on each floor, it is possible to use that number as a coefficient in the allocation evaluation, shortening the average waiting time. Also, when a user passes through a gate, the time the user will arrive at the elevator hall, the number of people waiting, and other circumstances can be known, so that the situation can be reflected in the allocation evaluation, making it possible for cars to respond efficiently.

On the other hand, if the estimation results are given to a building management company, for example, it will be possible to effectively use various functions related to building management, taking into consideration the traffic demand of the entire building.

According to at least one embodiment described above, it is possible to provide a car estimation device and a car estimation method that can estimate a car in which a user rides without requiring a dedicated device.

In addition, in the above embodiment, the security gates installed on each floor were used to obtain the passing information of the users, but it is also possible to obtain the passing information of the users by using existing devices such as surveillance cameras. You can also try to get it.

In summary, although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents as set forth in the claims.

100...building, 101, 102, 103...elevator hall, 110...elevator system, 111a to 111f...cars, 112a to 112f...control panel, 113...group management control device, 120...entrance/exit control system, 121, 124...entrance/exit gates, 122, 123...floor gates, 200...car estimation device, Ta...departure floor gate passing time, Tb...hall arrival time, Tc...boarding time, Td...disembarking time, Te...arrival floor gate passing time, t1...walking time, t2...waiting time, t3...boarding Car time, t4...walking time, e1...estimated walking time, e2...estimated hall arrival time, e3...estimated disembarking time, e4...estimated walking time, 501...arrival time distribution, 502...disembarking time distribution, 810...user data, 820...elevator operation data, 801...user data acquisition unit, 802...user data aggregation and conversion unit, 803...operation data acquisition unit, 804...operation data conversion unit, 805...estimation processing unit, 806...arithmetic processing unit, 807...output conversion processing unit, 808...data output unit, 830...output data.

The user data acquisition unit is configured to determine a first time when the user passes through a first authentication device installed at the entrance side of the elevator hall on the first floor of the building, and a time that is different from the first floor. Obtain user data including a second time when the user passed through a second authentication device installed on the exit side of the elevator hall on the second floor. The operation data acquisition unit acquires operation data of a plurality of cars installed in the building. The estimation processing unit determines whether the user has boarded the car in each car based on the user data acquired from the user data acquisition unit and the driving data acquired from the driving data acquisition unit. Estimate the car and the operating section. The data output section outputs the result estimated by the estimation processing section in a predetermined data format.

Claims (11)

User data that obtains user data including a first time when the user passes through a first floor in a building and a second time when the user passes through a second floor different from the first floor. an acquisition department;
an operation data acquisition unit that acquires operation data of a plurality of cars installed in the building;
Based on the user data acquired from the user data acquisition unit and the driving data acquired from the driving data acquisition unit, the car in which the user boarded among the plurality of cars is operated. an estimation processing unit that estimates an interval;
A car estimation device comprising: a data output section that outputs the result estimated by the estimation processing section in a predetermined data format. The estimation processing unit:
calculating a boarding probability indicating a probability that the user boards the elevator from the first floor for each of the plurality of elevator cars by estimating a time when the user arrives at the elevator hall of the first floor based on the first time;
calculating an alighting probability indicating a probability that the user alights at the second floor for each of the plurality of cars by estimating a time when the user alights at the second floor based on the second time;
The car estimation device as described in claim 1, characterized in that the car having the operating section among the multiple cars where the boarding and alighting probability obtained by multiplying the boarding probability and the alighting probability is the maximum value is estimated to be the car in which the user boarded. The estimation processing unit is
Based on the relationship between the first time distribution representing the time width of the estimated hall arrival time of the user on the first floor and the time when the plurality of cars start closing the doors on the first floor, Calculate the riding probability,
The disembarkation is determined based on the relationship between the second time distribution representing the time width of the estimated alighting time of the user on the second floor and the time when the doors of the plurality of cars are open on the second floor. 3. The car estimation device according to claim 2, wherein the car estimation device calculates a probability. the first time distribution is a normal distribution centered on a mean value of the estimated hall arrival times of the users;
4. The car arrival time estimation device according to claim 3, wherein the second time distribution is a normal distribution centered on a mean value of the estimated alighting times of the users. The first time distribution is created from a result of analyzing walking times of a required section on the first floor for each of a plurality of users;
4. The car load estimation device according to claim 3, wherein the second time distribution is created from a result of analyzing walking times for a required section on the second floor for each of a plurality of users. 2. The car estimation device according to claim 1, further comprising a first conversion section that aggregates the user data acquired from the user data acquisition section and converts the data into a format that can be processed by the estimation processing section. . 2. The car estimation device according to claim 1, further comprising a second conversion section that converts the driving data acquired from the driving data acquisition section into a format that can be processed by the estimation processing section. The estimation processing unit:
The elevator car aging estimation device according to claim 1, characterized in that the time when the user arrives at the elevator hall of the first floor, the time when the user boards the elevator car, and the time when the user disembarks at the second floor are output together with the estimated result of the elevator car. The car estimation device according to claim 1, further comprising a calculation processing unit that calculates the waiting time and number of users waiting for each floor based on the estimated car results of the estimation processing unit. 10. The car estimation device according to claim 9, further comprising a third conversion section that converts the output of the estimation processing section or the arithmetic processing section into a predetermined data format. Obtaining user data including a first time when the user passed through a first floor in the building and a second time when the user passed through a second floor different from the first floor;
Obtaining operational data of multiple cars installed in the building,
By estimating the time when the user arrives at the elevator hall on the first floor based on the first time, the user can board the elevator hall from the first floor for each of the plurality of cars. Calculate the riding probability that indicates the probability that
By estimating the time when the user gets off at the second floor based on the second time, the probability that the user gets off at the second floor for each of the plurality of cars is calculated. Calculate the probability of getting off the train,
estimating, among the plurality of cars, a car having an operating section where the probability of getting on and off obtained by multiplying the probability of getting on and getting off the car is the maximum value as the car in which the user boarded;
A method for estimating a passenger car.

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