JPH10194619A - Elevator OD table estimation device - Google Patents

Abstract

(57) [Summary] [PROBLEMS] To provide an OD table estimating device for a lift capable of obtaining an OD table that more accurately expresses the number of people getting on and off the floor. SOLUTION: Operation information of an elevator measured by a traffic measuring means 10 is stored in an operation information storage means 20, and knowledge stored in a knowledge storage means 50 and operation information of the elevator stored in the operation information storage means 20 are stored in the operation information storage means 20. On the basis of this, the row sum / column sum generation means 30 generates a row sum / column sum for the OD table to be estimated, and the prior OD table generation means 40 generates a prior OD table for the OD table. 60 is Gy 和 wa
An OD table that satisfies the constraint condition of the row sum / column sum generated by the column sum generation unit 30 and is closest to the prior OD table generated by the prior OD table generation unit 40 is estimated.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an elevator OD table estimating apparatus for estimating an OD table that can be used for grasping passengers on each floor during operation of the elevator.

[0002]

2. Description of the Related Art Generally, an OD table is a table showing the amount of traffic between any two of the transportation means for a multi-point transportation. FIG. 35 is an explanatory diagram of the OD table. The element xij of the OD table is from the starting point i to the arriving point j
Express traffic volume to. One point i of the two points is an origin and the other point j is an arrival point (destinatio).
n), origin-destination table or OD
It is called a table. In FIG. 35, the starting point is m and the arrival point is n.
This shows a case where there are a plurality of pieces. Of course, the points that are physically the same are i as the starting point and j as the arriving point,
They can have different numbers. The OD table is a basic data on the traffic volume of people and goods, and is one of the most important data used for designing traffic systems and improving services.

In many cases, it is difficult to measure each element xij of the OD table in terms of preparation time and cost. This is because it is virtually impossible to individually track where, where, and how much travel has taken place. The actual measurement is relatively easy, as shown in the following formulas (1), (2), and (3), the line sum xi. Are the column sum x.j, which is the sum of the traffic amounts arriving at the vehicle, and the total sum x .. of the traffic amounts.

[0004]

(Equation 1)

Therefore, when an OD table {xij} is required,
It is a practical method to measure xi., x.j, x .. and estimate from it. That is, each element xij, which is the contents of the OD table, is filled while the sum of the row sum and the column sum is adjusted. This is because the causal variable xij is the observed variable xi.
Indirect observations more than x.j. Therefore, by giving the missing information in the form of a priori probabilities, an attempt is made to make an estimation that matches the common sense as much as possible. The method is based on given distances between the a priori OD table {qij} and the estimated OD table {xij}, or an object with properties similar to the distance, under the equality constraints obtained from the given row sum / column sum. Minimizing the function,
For this purpose, an optimization method such as an iterative scaling method or an RAS algorithm can be used. In these methods, the estimate is obtained as a non-negative real number. That is, the result obtained is that, for example, there was only 0.73 traffic from point i to point j.

[0006] Also, it is often the case that the elements of the OD table are known to be limited to integers. For example, the traffic unit may be the number of cars, the number of ships, the number of luggage or containers, or the number of persons, or the number of connections of communication lines, the number of packets, or the like. In that case, rather than 0.73, I would like a prediction result expressed as an integer, such as 0 or 1 person. Therefore, recently, a method of performing estimation in a range of integers has appeared (for example, Japanese Patent Application No. 8-27431, “OD Table Integer Estimation Device”).

[0007]

By the way, when estimating the OD table in the transportation network of the elevator, the row sum xi. Required for the estimation is the number of passengers on the i-th floor, and the column sum x.j is the j-th floor. Corresponding to the number of people getting off at
It indicates the possibility of traffic to the floor. For accurate measurement of the number of passengers on each floor corresponding to row sum and column sum, there is no other method than direct observation by hand, and in such a case, it is very expensive. Therefore, in general, the number of people getting on and off each floor is calculated from a load change obtained as operation information of the elevator measured by the traffic measuring device of the elevator. The measurement of the load change can be realized at low cost by the load sensor.

When calculating a row sum and a column sum from a load change,
It is not always possible to accurately calculate the number of factories. This is because there is a problem that the weight distribution of the passengers varies, and a correct number of getting on and off can not be calculated from a load change when the getting on and off occurs at the same time. Therefore, there may be a contradiction that the measured sum of the number of passengers does not match the sum of the number of people getting off.

Since the conventional OD table estimating apparatus is a general-purpose apparatus and is not designed for an elevator, there is provided a means for automatically generating a row sum and a column sum based on operation information of the elevator. Did not. Therefore, in order to prepare the row sum and the column sum necessary for the estimation, the calculation of the number of getting on and off each floor based on the load change is performed manually or by another calculation device. Furthermore, since the conventional general-purpose OD table estimating device assumes only input data having no inconsistency in row sum and column sum, when applied to an elevator, the sum of the row sum and the sum of the column sum are different from each other. If did not match, OD table estimation was not possible.

A prior OD table, which is the other data necessary for OD table estimation, has a general form such as "if row sum xi. Is 0, all elements in row i of the prior OD table are 0". In addition to the above, in the case of an elevator, "No passengers get off on the same floor as the floor on which they got on.
Is always 0 ", which is specific to the elevator traffic network. Since the conventional OD table estimating apparatus does not include a means for automatically generating the prior OD table, the creation of the above-described prior OD table has conventionally been performed manually.

Further, in the generation of the row sum / column sum and the prior OD table, the more reliable row sum / column sum can be obtained by using the information of the operation direction, the hole button, and the car button obtained as the operation information. It is also possible to obtain a value or to specify an element that is definitely 0 and an element that is definitely not 0 among the elements of the prior OD table. For example, "If the elevator only works in the UP direction during the time of the OD table estimation target, there is no passenger getting off the floor below the floor on which the vehicle was boarded, so the lower left half qij (i> j) of the prior OD table is It is possible to specify the values of some elements of the prior OD table from the information on the traveling direction, such as "0." In the prior OD table, the more surely the element that is 0 and the element that is not 0 can be specified, and the more reliable the value of the row sum and the column sum can be generated,
It goes without saying that the accuracy of OD table estimation can be improved.

Normally, the OD table estimation is performed for a relatively long time of about 30 minutes to 1 hour (hereinafter referred to as O.D.
The period from the start to the end of the time to be estimated in the D-table estimation is referred to as an estimation target section), during which time the elevator repeatedly changes directions at short intervals of several minutes. Therefore, in order to generate the row sum / column sum and the prior OD table using the information of the button and the direction, and thereby improve the accuracy of the estimation, it is necessary to set one to 30 minutes.
For a long estimation target section over a period of time, information on buttons and directions is divided so that it can be easily used, and row sums, column sums, and prior OD tables are individually generated, and OD table estimation is performed. It is desirable to add up.

In the conventional general-purpose OD table estimating apparatus, no consideration has been given to performing such data division, OD table estimation based on the divided data, and totalization thereof. For this reason, the OD table estimation with the above-described data division, for which an improvement in accuracy is desired, has to be performed manually, which requires a great deal of labor and time.

As described above, the conventional general-purpose OD table estimating apparatus is not considered to be suitable for estimating the OD table of the elevator, and thus has the following disadvantages. (1) The row sum / column sum and the prior OD table cannot be automatically generated based on the operation information of the elevators.
The work of generating the column sum and the prior OD table had to be manually performed separately. (2) If there is a contradiction between the row sum and the column sum, it is impossible to estimate the OD table. (3) Since only the OD table estimation can be performed collectively, the OD table estimation that can improve the estimation accuracy by dividing the estimation target section cannot be realized.

An object of the present invention is to provide an OD table estimating apparatus for an elevator, which can obtain an OD table that more accurately expresses the number of passengers on each floor.

[0016]

According to a first aspect of the present invention, there is provided an elevator OD table estimating apparatus for measuring traffic information of an elevator, and operating the traffic information of the elevator measured by the traffic measuring means. Information storage means, and knowledge storage means for storing knowledge used when generating a row sum / column sum for the OD table to be estimated from the operation information of the elevator stored in the operation information storage means and a prior OD table, Utilizing the knowledge stored in the knowledge storage means, the row sum and the OD table to be estimated from the operation information of the elevator stored in the operation information storage means
A row sum / column sum generation means for generating a column sum, and a priori OD table for an OD table to be estimated from the operation information of the elevator stored in the operation information storage means using the knowledge stored in the knowledge storage means. A prior OD table generating means for generating, and an OD that satisfies the constraint condition of the row sum / column sum generated by the row sum / column sum generating means and is closest to the prior OD table generated by the prior OD table generating means OD table estimating means for estimating a table.

In the OD table estimating device for a lift constructed as claimed in claim 1 of the present invention, the operation information of the elevator within the target time for the OD table estimation is measured by the traffic measuring means, and the measured operation information is used for the operation. Stored in the information storage means. OD to be estimated from the operation information of the elevator stored in the operation information storage means
The knowledge required to generate the row sum / column sum for the table and the a priori OD table are stored in the knowledge storage means in advance. The row sum / column sum generation means refers to the knowledge stored in the knowledge storage means and performs O / O based on the operation information stored in the operation information storage means.
A row sum and a column sum necessary for performing the D table estimation are generated. The prior OD table generation means generates a prior OD table necessary for estimating the OD table based on the operation information stored in the operation information storage means while referring to the knowledge stored in the knowledge storage means. . Thereafter, the OD table estimating means uses the row sum / column sum generated by the row sum / column sum generating means and the prior OD table generated by the prior OD table generating means by using a known optimization method.・ Satisfies the constraint condition of column sum and prior OD
Estimate the OD table closest to the table.

According to a second aspect of the present invention, in the OD table estimating device for an elevator, the knowledge storage means stores the knowledge to be stored with a priority added thereto,
The column sum generation unit and the prior OD table generation unit may be configured to generate a row sum / column sum and a prior OD table when data generation based on different knowledge in the knowledge storage unit results in inconsistency. , A row sum, a column sum, and a prior OD table are generated by employing a data generation result based on high-priority knowledge.

[0019] The OD of the elevator constructed as in claim 2
In the table estimating device, in addition to the operation of the OD table estimating device of the elevator according to the first aspect, the knowledge stored in the knowledge storage means is stored with a priority added. Further, the row sum / column sum generating means may generate the row sum / column sum by a plurality of methods based on different knowledge stored in the knowledge storage means when generating the row sum / column sum. If possible, generate multiple row sums and column sums using all possible methods and compare the results.If all the generated results are the same, use the same value as the generated result. When a plurality of generation results are different, the priorities of the knowledge used for each generation are compared, and a row sum or a column sum generated based on the knowledge having a higher priority is adopted as the generation result. In addition, the prior OD table generation means,
When generating the prior OD table, the prior OD table can be obtained by a plurality of methods based on different knowledge stored in the knowledge storage means.
If it is possible to generate the elements of the table, generate a plurality of elements of the prior OD table in all possible ways and compare the results, and if the plurality of generated results are all the same, the same Value is adopted as the generation result, and when two or more generation results are different, the priority of the knowledge used for each generation is compared, and the value generated based on the high priority knowledge is generated for the element. Adopt as a result.

According to a third aspect of the present invention, in the elevator OD table estimating apparatus according to the first aspect of the present invention, there is provided a hall number detecting means for detecting the number of customers in the hall of the elevator and calculating the number of people getting on and off. The row sum generation means replaces the row sum / column sum generated from the operation information with the row sum / column calculated by the hall number detection means for the floors for which the number of boarding passengers can be calculated by the hall number detection means. It is intended to be a sum.

In the OD table estimating device for a lift constructed as in claim 3, in addition to the operation of the OD table estimating device for the elevator according to claim 1, the hall number detecting means may include a cage arriving at the stop floor. The number of halls (the number of passengers in the hall) before and after departure is detected. Further, based on the detected number of halls before arrival and after departure, the number of people getting on and off the floor is calculated. In addition, the row sum / column sum generation means, when generating the row sum / column sum, for the floor on which the number of boarding / disembarking persons can be calculated by the hall number detection means, uses the row sum generated from the operation information by the hall number detection means. Replace with the calculated number of passengers,
In addition, the row sum generated from the operation information is replaced with the number of descendants calculated by the hall number detection means to obtain a final row sum / column sum.

According to a fourth aspect of the present invention, there is provided an elevator OD table estimating apparatus according to the first aspect of the present invention, further comprising a passenger input / output number input means for inputting the number of passengers entering and exiting the hall of the elevator. The generation means replaces the row sum / column sum generated from the operation information with the number of passengers entered / exited from the passenger input / output number to obtain the row sum / column sum for the floor on which the number of passengers is input from the passenger input means. It is like that.

The OD of the lift configured as in claim 4
In the table estimating device, in addition to the operation of the OD table estimating device of the elevator according to claim 1, the number of passengers obtained by means other than the traffic measuring means is input to the passenger input / output means. Also,
The row sum / column sum generation means generates the row sum / column sum when generating the row sum / column sum only on the floor where the number of passengers is entered in the passenger input / output number input means, based on the operation information measured by the traffic measurement means. The sum is replaced with the number of passengers entered from the passenger input means to obtain a row sum and a column sum.

According to a fifth aspect of the present invention, in the elevator OD table estimating apparatus according to the first aspect, the row sum / column sum generation means generates the row sum / column sum based on the operation information of the elevator stored in the operation information storage means. If the sum of the row sums and the sum of the column sums do not match, the sum of the row sums and the sum of the column sums are corrected so that the sum of the row sums and the sum of the column sums match. Correction means is provided, and the OD table estimation means performs OD table estimation based on the row sum / column sum corrected by the row sum / column sum correction means and the prior OD table generated by the prior OD table generation means. It is like that.

The OD of the elevator constructed as in claim 5
In the table estimating device, in addition to the operation of the OD table estimating device of the elevator according to claim 1, when there is a contradiction between the row sum and the column sum generated by the row sum / column sum generating means, the row sum / column sum correction is performed. Means are
The row sum and the column sum are corrected so as to eliminate the contradiction.

According to a sixth aspect of the present invention, in the elevator OD table estimating apparatus according to the fifth aspect, the row sum / column sum correction means includes a sum of row sums generated by the row sum / column sum generation means. Sum calculation means for calculating the difference between the sum of the sum of the sum of the column sum and the sum of the sum of the columns; a correction target selection means for selecting which of the row sum and the column sum is to be corrected; Correction value calculation means for calculating a correction value that needs to be added or subtracted to eliminate the sum difference for each element of the row sum or the column sum, and the elements in order of value from the row sum or the column sum to be corrected Are selected one by one, and the correction value calculated by the correction value calculation means is added or subtracted to or from the value of the selected element until the difference between the sum of the row sum and the sum of the column sum disappears. Row and column sum updating means for updating.

[0027] The OD of the elevator constructed as in claim 6
In the table estimating device, in addition to the operation of the OD table estimating device for the elevator according to claim 5, the sum total difference calculating means of the row sum / column sum correcting means includes the sum of the row sum generated by the matrix / column sum generating means and the column sum. Calculate the difference between the sums of the sums. Next, the correction target selecting means selects which of the row sum and the column sum is to be corrected. next,
The correction value calculating means calculates a correction value that needs to be added or subtracted for each row sum or column sum element to be corrected selected by the correction target selecting means in order to eliminate the sum difference. Next, the row sum / column sum update means selects one element having the largest value from the row sum or the column sum to be corrected, and calculates a correction value for the selected element calculated by the correction value calculation means for the element. , The value of the selected element is updated. Subsequently, the sum difference calculating means calculates the sum difference between the row sum and the column sum after updating the element values. as a result,
If the total difference is 0, the correction ends. If the total sum difference is not 0, the row sum / column sum update means again selects one element having the largest value among the elements which have not been selected yet, and sets the correction value calculated by the correction value calculation means to that element. The value of the selected element is updated by adding or subtracting from. Next, the sum difference calculating means compares the sum difference between the updated row sum and the column sum. This is repeated until the total difference becomes zero.

According to a seventh aspect of the present invention, in the elevator OD table estimating apparatus according to the sixth aspect, the correction target selecting means selects “always select a row sum as a correction target”.
"Always select the column sum as the correction target", "Select the row sum or the column sum with the larger total sum as the correction target",
"Select the row sum or column sum with the smaller sum as the correction target.", "Select the sum difference between the row sum and the column sum if the even number is larger, and the odd sum is the smaller sum. , Select as a correction target '' or `` row sum, sum total difference of column sum, if the odd number is the larger sum, if the even sum is smaller, select the smaller sum as the correction target '',
It is configured to select which of the row sum and the column sum is to be corrected.

[0029] The OD of the elevator constructed as in claim 7
In the table estimating device, in addition to the operation of the OD table estimating device for the elevator according to claim 6, the correction target selecting means “always selects a row sum as a correction target” and “always selects a column sum as a correction target”. , "Select the larger sum of the row sum and the column sum as the correction target", "Select the smaller sum of the row sum and the column sum as the correction target", "Select the sum difference of the row sum and the column sum However, in the case of an even number, the larger sum is selected, in the case of an odd number, the smaller sum is selected as a correction target, or `` the sum difference between the row sum and the column sum is larger. ,
In the case of an even number, the smaller sum is selected as the correction target ", and which of the row sum and the column sum is to be corrected is selected.

According to an eighth aspect of the present invention, there is provided the elevator OD table estimating apparatus according to the first aspect, wherein the operation information of the elevator stored in the operation information storage means is divided into a plurality of pieces according to a predetermined standard. An information dividing unit and an estimated OD for summing up the results of the OD table estimation by the OD table estimating unit for each piece of the operation information divided by the operation information storage unit.
Table summing means, row sum / column sum generation means and prior OD
The table generation means sequentially generates a row sum / column sum and a priori OD for each division unit based on each operation information divided by the operation information division means, and the OD table estimating means includes a row sum / column sum generation means and Row sum / column sum generated by the prior OD table generating means and the prior O
The OD table estimation is sequentially performed for each division unit based on the D table.

[0031] The OD of the elevator constructed as in claim 8
In the table estimating device, the operation information of the elevator is measured by the traffic measurement means and stored in the operation information storage means. Next, the operation information dividing means divides the operation information of the elevator stored in the operation information storage means into a plurality of pieces according to a predetermined standard. The OD table estimation is sequentially performed on each piece of the operation information divided by the operation information dividing means as follows. The row sum / column sum generation means,
While referring to the knowledge stored in the knowledge storage means, the operation information for one unit divided by the operation information
Generates row sum and column sum necessary for performing table estimation. The a priori OD table generating means is a priori OD table necessary for estimating an OD table from one unit of operation information divided by the operation information dividing means while referring to the knowledge stored in the knowledge storage means. Generate Thereafter, the OD table estimating means calculates the row sum / column sum generated by the row sum / column sum generating means and the prior O
From the prior OD table generated by the D table generation means, using a known optimization technique, satisfy the constraint conditions of row sum and column sum,
The OD table closest to the prior OD table is estimated. Estimated OD
The table totaling means adds and totals the OD table estimation results obtained by the OD table estimating means. Such an operation is repeated until the OD table estimation for all of the operation information divided by the operation information dividing means is completed, and the OD table estimation result during that time is estimated.
The D-table totaling means builds up an estimated OD table for the entire estimation target section.

In the OD table estimating device for a lift according to the ninth aspect of the present invention, in the invention according to the eighth aspect, the operation information dividing means stores the operation information of the elevator stored in the operation information storage means into the UP of the lift. , DOWN directions.

[0033] The OD of the elevator constructed as in claim 9
The table estimating device constructs the estimated OD table by the same operation as the OD table estimating device for the elevator according to claim 8, but the operation information dividing means updates the operation information of the elevator stored in the operation information storage means to UP, It is divided into two according to the direction of DOWN.

According to a tenth aspect of the present invention, in the elevator OD table estimating apparatus according to the eighth aspect, the operation information dividing means stores the operation information of the elevator stored in the operation information storage means in accordance with the traveling direction. The same space is divided as one unit.

According to a tenth aspect of the present invention, the O
The D table estimating device constructs the estimated OD table by the same operation as the OD table estimating device of the elevator according to claim 8, but the operation information dividing means uses the operation information of the elevator stored in the operation information storage means, The unit is divided as a unit while the traveling direction is the same.

According to an eleventh aspect of the present invention, in the elevator OD table estimating apparatus according to the eighth aspect of the present invention, the operation information dividing means includes the operation information of the elevator stored in the operation information storage means, In this case, the state until the state is returned from 0 to the state of 0 is divided as one unit.

According to the eleventh aspect of the present invention, the O
The D table estimating device constructs the estimated OD table by the same operation as the OD table estimating device of the elevator according to claim 8, but the operation information dividing means uses the operation information of the elevator stored in the operation information storage means, The unit is divided into one unit until the load returns to the state of 0 from the state of 0 again.

[0038]

Embodiments of the present invention will be described below. FIG. 1 is a block diagram of an OD table estimating apparatus 1 for a lift according to the first embodiment of the present invention.

The OD table estimating device 1 of the elevator is used for measuring traffic information (eg, traveling direction, load, position, car button information, hole button information, etc.) of the elevator, and the traffic measured by the traffic measuring means 10. The operation information storage means 20 for storing information, and the knowledge used when generating the row sum / column sequence and the prior OD table for the OD table to be estimated from the traffic information of the elevator stored in the operation information storage means 20 are described. A row for generating a row sum and a column sum for an OD table to be estimated from the operation information of the elevator stored in the operation information storage means using the knowledge stored in the knowledge storage means to be stored and the knowledge stored in the knowledge storage means. Utilizing the knowledge stored in the knowledge storage means 50 and the sum / column sum generation means 30, a prior OD table for an OD table to be estimated from the operation information of the elevator stored in the operation information storage means 20 is generated. A priori OD table generation means 40 and a predetermined optimization method based on the row sum / column sum generated by the row sum / column sum generation means 30 and the prior OD table generated by the prior OD table generation means 40 OD table estimating means 60 that satisfies the constraint condition of the row sum / column sum and estimates the OD table closest to the prior OD table.

The traffic measuring means 10 measures the traffic condition of the elevator for which the OD table is to be estimated for a specified period of time.
The operation information of the elevators measured by the traffic measuring means 10 is, for example, the following items. (1) Arrival time Arrival time to stop floor (2) Stop floor Arrival floor name (3) Car button ON / OFF state of car button immediately before arrival time (4) Hall button Hall on stop floor immediately before arrival time Button ON / OFF state (5) Load (at arrival) Load in the car at arrival (6) Load (minimum value) Minimum value of load change in the car during stoppage at the stop floor (7) Load (at departure ) Load in the car at the time of departure (8) Direction of travel The direction of travel of the car after departure from the stop floor The contents of the above items will be briefly described. Hereinafter, for the sake of simplicity, the description will be made assuming that the object of the OD table estimation is a five-story building. The arrival time is the arrival time at the stop floor and is expressed in hours, minutes, and seconds. The stop floor is one of the first to fifth floors. The car button is a button for the passenger to enter the destination floor in the car of the elevator. In the case of a five-story building as an example, five buildings correspond to the first to fifth floors, respectively.
There are two basket buttons. The initial state of the basket button is all O
FF. The button pressed by the passenger in the car is turned ON, and returns to the OFF state after arriving at the target floor. In the state measurement of the car buttons in the first embodiment, the states of the five car buttons immediately before the car arrives at a certain floor are measured and recorded.

The hall button is a button for the passenger to call the elevator, and is located on each floor from the first floor to the fifth floor.
UP hole button and D to be pressed when you want to go to P direction
There is a DOWN hole button that is pressed when it is desired to go in the DOWN direction. Only the UP hall button is on the first floor of the lowest floor, only the DOWN hall button is on the fifth floor of the top floor, and both the UP and DOWN hall buttons are on the second to fourth floors, which are the middle floors. . The initial state of the hole buttons is all OFF. The button pressed by the passenger in the hall is O
The car enters the N state, and the car that answers the request (the car that moves in the UP direction if the UP hall button is ON) arrives at the floor of the hall button and then returns to the OFF state. In the measurement of the state of the hall buttons in the first embodiment, the UP, DO,
Measure and record the state of the two hole buttons of WN.

The load changes as passengers get on and off while the car is stopped on the stop floor and the door is open. This first
In this embodiment, the minimum load is measured and recorded at the time of arrival, departure, and while the car is stopped at the stop floor. The traveling direction is either UP or DOWN. The traveling direction may differ before and after the arrival of the basket. In the first embodiment, only the direction after departure is measured and recorded.

All of these items are information measured by a sensor or the like in a general elevator system and used for controlling the operation of the elevator. FIG. 2 shows an example of the operation information of the elevator stored in the operation information storage means 20 as a result of measuring these items.

In the traffic measurement for estimating the OD table of the elevator, the measurement is often performed in units of 30 minutes or 1 hour. However, in order to simplify the explanation, in the example shown in FIG. It shows a short time as a measurement target. In the table, the measured states of the car button and the hole button are represented by 0 and 1. 0 is OFF state, 1
Means ON state. The first row of the table reads, "The car arrives at the first floor at 8: 00: 00: 00, all five car buttons immediately before arrival to the first floor are OFF, the first floor hall button is the UP hall button ON, and the DOWN hall is the DOWN hall. The button is in the OFF state, the load when arriving at the first floor is 0 kg, the load at the time of departure is 110 kg, the minimum load during stoppage is 0 kg, and the car proceeds in the UP direction after departure. " Is shown. The same applies to the second and subsequent lines.

Next, FIG. 3 shows the knowledge stored in the knowledge storage means 50 in advance. This knowledge is based on row sum, column sum,
This is the knowledge when generating the D-table, and the operation information storage means 20
Is used to generate a row sum / column sum and an a priori OD table for the OD table to be estimated from the operation information of the elevator stored in the OD table. The generation knowledge of the row sum / column sum and the prior OD table shown in FIG. 3 includes knowledge for calculating the row sum / column sum and knowledge for determining the elements of the prior OD table.

The knowledge for calculating the number of getting on and off at each floor includes the row sum and the column sum (that is, the row sum and column sum necessary for the OD table estimation based on the load change which is one of the operation information stored in the operation information storage means 20). A calculation formula for calculating the number of people on each floor and the number of people getting off) and values of constants used for the calculation are described. The symbol [] in the calculation formula indicates a process in which a fractional part of a real number surrounded by [] is rounded down to an integer. For example, [3.2] = 3.

The knowledge for determining the elements of the prior OD table includes:
The knowledge for determining the value of each element of the prior OD table is described. The knowledge g1. Is the knowledge that "the diagonal element qii of the prior OD table is always 0". This knowledge is derived from the characteristics of the traffic flow of elevators, "No passengers get off on the same floor as the floor on which they got on." Also, knowledge d1.
"If the traveling direction is always UP during the time of the measurement object, the element of qij (i <j) of the prior OD is always 0."
It represents knowledge. This knowledge also states that "passengers traveling by elevators in the UP direction are always on the floor that descends from the floor on which they have ridden, and while the direction is UP, the floors from i to j (where i <
There is no possibility that inter-story traffic to j) will occur. "

After the operation information measured by the traffic measurement means 10 is stored in the operation information storage means 20, the row sum / column sum generation means 30 outputs the row sum / column sum stored in the knowledge storage means 50.
The row sum and the column sum are generated from the operation information stored in the operation information storage unit 20 by using the knowledge for calculating the column sum. The prior OD table generation means 40 uses the knowledge for element determination of the prior OD table stored in the knowledge storage means 50 to derive the prior OD from the operation information stored in the operation information storage means 20. Generate table generation knowledge.

An example of generating a row sum / column sum by the row sum / column sum generation means 30 will be described. Based on the data in the first row of FIG.
To calculate the number of passengers on the first floor, the following calculation is performed using knowledge c1, knowledge c2, and knowledge l2.

The number of passengers = [(110−0 + 30) / 60] = 2 Thus, the number of passengers 2 on the first floor is obtained, and the row sum of the first row necessary for OD table estimation is obtained.

By the way, in the operation information shown in FIG.
Since there is only one stop on the floor, the number of passengers on the first floor can be obtained by simply performing the above calculation. However, if there are multiple stops on the first floor in the operation information, the above calculation must be performed on the first floor. The number of riders on the first floor in the target section is obtained by repeating the number of stops and summing up the results. FIG. 4 shows the row sum / column sum generated by the row sum / column sum generation means 30 from the traffic information in FIG. 2 in this manner.

Next, an example of generation of the prior OD table by the prior OD table generation means 40 will be described. Since the building to be estimated has five floors, the prior OD table is a matrix of 5 rows and 5 columns, and its elements are 2
There are five. First, the prior OD table generation means 40 initializes all elements of the prior OD table to 1. Here, all elements are set to 1 as an initial value in order to indicate a state that all inter-story traffic may occur at the same ratio, but this is not necessarily 1. The initialized prior OD table is shown in FIG.

Next, the prior OD table generating means 40 sequentially refers to the knowledge for determining the elements of the prior OD table in the knowledge storage means 50, and determines the values of the elements of the prior OD table based on the knowledge. Update. First, a priori O updated with reference to knowledge g1.
Table D is shown in FIG. The value of the diagonal element qii (i = 1,..., 5) has been changed to 0. Next, FIG. 7 shows an a priori OD table updated with reference to the knowledge g2. Since the row sum of the fourth row (that is, the number of passengers on the fourth floor) is 0 in the row sum generation result, the value of q4j (j = 1,..., 5) has been changed to 0. Next, FIG. 8 shows an a priori OD table updated with reference to the knowledge g3. In the generation result of the column sum, the column sum of the first column (that is, the number of descendants on the first floor) is 0, so that qi1 (i
= 1,..., 5) has been changed to 0. Subsequently, the knowledge d1. And the knowledge d2. Are sequentially referred to.

In this example, since the direction is both UP and DOWN during the target time, the condition that the direction of knowledge d1. Is always UP and that of knowledge d2. Not applicable. Therefore, knowledge d1.,
The value of the element of the prior OD table is not updated using the knowledge d2. In this way, a prior OD table is generated.

According to the above procedure, the row sum / column sum generation means 3
FIG. 9 shows the row sum / column sum generated by 0 and the prior OD table generated by the prior OD table generation means 40. The content of the table is the generated prior OD table, and the row sum / column sum column shows the generated row sum,
Each contains a column sum. Here, the row sum and the column sum column do not include the row sum and the column sum of the prior OD table. For example, the sum of the rows in the second row of the prior OD table is 3,
It is not 1 in the row sum column. That is, the row sum and the column sum of the prior OD table are not recorded.

In this way, the row sum / column sum and the prior OD
After the table is generated, the OD table estimating means 60 estimates the OD table that satisfies the constraints derived from the generated row sum / column sum and is closest to the prior OD table by using a predetermined optimization method. . FIG. 10 shows an estimation result when the OD table estimating means 60 performs the OD estimation by employing the calculation method by the same applicant's already-filed Japanese Patent Application No. 8-27431 “OD table integer estimating device”. .

As described above, according to the first embodiment, the row sum / column sum necessary for estimating the OD table and the prior OD table are automatically generated based on the operation information of the elevator. OD table estimating device of the elevator which can perform the above.

Next, a second embodiment of the present invention will be described. FIG. 11 is an explanatory diagram of the generation knowledge of the row sum / column sum and the generation knowledge of the prior OD table stored in the knowledge storage unit 50 according to the second embodiment of the present invention.

The knowledge storage means 5 in the second embodiment
0 indicates that it is possible to add a priority to the knowledge to be stored, and the row sum / column sum generation means 30 and the prior OD table generation means 40 execute the row sum / column sum calculation based on the knowledge in the knowledge storage means 50.
When generating a column sum and an a priori OD table, if data generation based on different knowledge results in inconsistency, a result based on knowledge with higher priority is adopted.

The operation information of the elevator is measured by the traffic measuring means 10 in the second embodiment, the measured operation information is stored in the operation information storing means 20, and the traffic sum is generated by the row sum / column sum generating means 30. OD table estimation performed by the OD table estimating means 60 from the sum of rows and columns and the prior OD table generated by the prior OD table generating means 40 is performed in the same manner as in the first embodiment.

The knowledge stored in the knowledge storage means 50 can be given a priority. This knowledge storage means 5
FIG. 11 shows an example of the knowledge to which the priority stored in “0” is added.
Shown in In this example, only the generated knowledge for calculating the row sum and the column sum is shown. However, priority can be similarly added to the knowledge for determining the elements of the prior OD table. In this example, the content of the knowledge h1. Will be described.

The knowledge h1. Is described as follows: “The traveling direction of the basket is UP,
If the UP hall button on the kth floor immediately before the car arrives at the kth floor is OFF and the number of riders on the kth floor (calculated from the change in load) is not 0, the number of riders on the kth floor is set to 0. , And the number of people getting off is {number of people getting off (calculated from load change) −number of people getting on (calculated from load change)}. UP (k) in the knowledge indicates the state of the UP hall button on the kth floor immediately before the car arrives at the kth floor by DOWN.
(K) indicates the state of the DOWN hall button on the kth floor immediately before the car arrives at the kth floor.

The knowledge h1.
Since the state is that there should be no passengers coming from that floor, from the calculation based on the load change, even if it seems that the number of passengers is occurring, the number of passengers measured there is not the other passengers It is more likely that the passengers once got off the basket to get off the vehicle and boarded again, that is, passengers who did not actually get off on that floor. Therefore, the actual number of passengers is set to 0, and the number of people getting off is obtained by subtracting the number of people who have not actually got off (= the apparent number of people riding) from the number of people getting off. This is the knowledge derived from the characteristics of elevator traffic flow. Knowledge h2., Knowledge h3., Knowledge h
4 is a similar idea, and it is knowledge derived from the characteristics of elevator traffic flow.

A priority "10" is added to the knowledge h1. The priority indicates that the higher the numerical value, the higher the priority. The row sum / column sum generation means 30 and the prior OD table generation means 40 generate the row sum / column sum and the prior OD table,
When data generation based on different knowledge results in inconsistent results, a result based on knowledge with higher priority is adopted. For example, the row sum, derived from knowledge h1.
If the generation result of the column sum is different from the generation result of the row sum / column sum derived by the knowledge l1 having the priority “0”, the knowledge h1.
Is used as the final generation result.

As an example of data generation using such priorities, the operation information shown in FIG.
An example of generating a row sum / column sum by the row sum / column sum generation means 30 when the sum is stored in 0 will be described below. The row sum / column sum generation means 30 calculates the number of passengers at each stop floor based on the data of each row in FIG. For example, when calculating the number of passengers on the fourth floor based on the data in the fourth row, the knowledge c1., Knowledge c2., Knowledge l1, and knowledge awareness l2. The number of people and the number of people getting off are calculated as follows.

The number of passengers = [(60−0 + 30) 60] = 1 The number of passengers = [(176-0 + 30) / 60] = 3 On the other hand, based on the knowledge h1.
The number of passengers on the floor and the number of people getting off are calculated as follows.

As described above, when the number of passengers getting on and off and the number of passengers getting off and on = 3-1 = 2 are different from the number of passengers getting on and off based on the knowledge l1. The sum / column sum generation means 30 compares the priorities of both knowledges, and outputs the result derived by the knowledge h1.
Adopted as the number of getting on and off the floor. Prior OD table generation means 40
In the generation of an a priori OD table according to the above, if the generation of elements of the a priori OD table based on different knowledge results in contradictory results, the result based on the high priority knowledge is adopted.

According to the second embodiment, the row sum / column sum necessary for estimating the OD table and the prior O
When generating a D-table, even if the generation results differ depending on the knowledge used for data generation, it is possible to resolve the inconsistency and uniquely determine the data generation results.

Next, a third embodiment of the present invention will be described. FIG. 13 is a block diagram of an OD table estimating device for a lift according to the third embodiment of the present invention. OD table estimating device 1 for a lift according to the third embodiment
Is a configuration obtained by adding a row sum / column sum correction unit 70 to the first embodiment shown in FIG. The row sum / column sum correction unit 70 calculates the sum of the row sum / column sum in the row sum / column sum generated by the row sum / column sum generation unit 30 based on the operation information of the elevator stored in the operation information storage unit 20. If the sums of the column sums do not match, the row sum and the column sum are corrected so that the sum of the two sums up.

The row sum / column sum corrector 70 includes a sum difference calculator 80 for calculating a difference between the sum of the row sums generated by the row sum / column sum generator 30 and the sum of the column sums; Correction target selecting means 90 for selecting which of the sums is to be corrected,
Correction value calculation means 1 for calculating a correction value that needs to be added or subtracted in order to eliminate a sum difference for each element of a row sum or a column sum which is a correction target selected by the correction target selection means 90
00, and select elements one by one from the row sum or the column sum to be corrected in descending order of value, and select the correction value calculated by the correction value calculation means until there is no difference between the sum of the row sums and the sum of the column sums Row and column sum updating means 110 for adding or subtracting the value of the selected element to update the value of the selected element.

The sum difference calculating means 80 calculates the difference between the sum of the row sums and the sum of the column sums.
The difference between the sum of the row sum and the sum of the column sum calculated by is input to the correction value calculation means 100. The correction value calculating means 100 calculates a correction value for the row sum or the column sum selected by the correction target selecting means 90. That is, the correction value calculating means 100
Is calculated based on the difference between the sum of the row sum and the sum of the column sum calculated by the sum difference calculating means 80 for each element of the row sum or the column sum selected by the correction target selecting means 90. The correction value that needs to be added in order to eliminate is calculated. The row sum / column sum update unit 110 selects one element at a time from the row sum or the column sum selected by the correction target selection unit 90 in the order of larger value, and selects the elements calculated by the correction value calculation unit 100. The correction value for the element thus added is added to that element, and this is repeated until the row sum or the column sum after the addition update becomes a value that eliminates the total sum difference.

The OD table estimating means 60 estimates the OD table based on the row sum / column sum corrected by the row sum / column sum correcting means 70 and the prior OD table generated by the prior OD table generating means 40. I do. Other configurations are the same as those of the first embodiment shown in FIG. 1, and therefore, the same components are denoted by the same reference numerals and description thereof will be omitted. That is, the measurement of the operation information of the elevator by the traffic measurement unit 10 and the storage of the measured operation information in the operation information storage unit 20 in the third embodiment are as follows.
This is performed in the same manner as in the first embodiment. Knowledge storage means 5
0 in FIG. 3 in the first embodiment.
Is the same as the knowledge stored in the knowledge storage means 50 shown in FIG. In addition, the row sum / column sum generation unit 30 and the prior OD table generation unit 40 refer to the knowledge in the knowledge storage unit 50 and execute the row sum / column sum Generate a test OD table.

FIG. 14 shows an example of the row sum / column sum and the prior OD table generated by the row sum / column sum generation means 30 in the third embodiment. This example shows a case where the floor is the 14th floor. In the row sum / column sum and the prior OD table shown in FIG. 14, the total sum of the generated row sums is 2324.
Thus, the sum of the column sums is 2344, and the sums of the two do not match. The calculation of the number of passengers getting on and off from the load change has a problem that the weight distribution of the passengers varies, and there is a problem that the correct number of getting on and off can not be calculated from the load change when getting on and off at the same time. It is not always possible to calculate the number of getting on and off each floor. Therefore, a situation may occur in which the sum of the generated row sum and column sum does not match.

When the sum of the row sums and the sum of the column sums generated by the row sum / column sum generation means 30 do not match,
The row sum / column sum correction unit 70 performs correction by the following method so that the total sum of the row sums and the total sum of the column sums match. First, the sum difference calculating means 80 calculates the difference between the sum of the row sums and the sum of the column sums. In this example, “20” is calculated as the sum difference. Next, the correction value calculating unit 100 calculates a correction value that needs to be added to each element of the row sum or the column sum based on the total difference between the row sum and the column sum in order to eliminate the total difference. In the third embodiment, the correction target selecting means 90 includes:
It is assumed that the smaller of the sum of the row sum and the sum of the columns is set as a correction target. In this case, the correction value calculating means 100
Means that the correction is performed by adding a correction value to each of the elements having the smaller total sum to be corrected.

Here, the method of determining the correction target is not limited to this. For example, the one having the larger sum of the row sum and the column sum is set as the correction target, and the correction value is set for each of the correction target elements. The correction may be performed by pulling. Also, it is determined whether the smaller sum is to be corrected or the larger one is to be corrected depending on whether the sum difference is even or odd.For example, if the sum difference is even, the smaller sum is used as the sum difference. In the case of an odd number, there is also a method in which the one having the larger sum is to be corrected. Further, there is a method in which either the row sum or the column sum is always the target of correction.

In the example shown in FIG. 14, since the sum of the row sums is smaller, the row sums are to be corrected in the second embodiment. The correction value for the i-th row sum is calculated by the following equation.

[0077]

(Equation 2)

The symbol <> in the expression means that the decimal part of the real value in <> is rounded up to an integer. For example,
<2.4> = 3. When the correction value for 7 which is the row sum of the first row is calculated by the above equation, the following is obtained, and the correction value “1” is obtained.

Correction value of row sum of first row = <20 * (7/2324)> = <0.0602409> = 1 Correction value for each element of row sum to be corrected obtained by such calculation FIG. 15 shows the calculation result of.

Next, the row sum / column sum updating means 110 selects elements one by one from the row sum to be corrected one by one in descending order of value, and adds a correction value for the selected element to the element. In the case of the example illustrated in FIG.
82 is selected as the maximum element, and the correction value 18 is added. Thus, the row sum of the second row is updated to 2000, and the sum of the row sums is updated to 2342. FIG. 16 shows the updated row sum after the addition of the correction value.

Here, the sum difference calculating means 80 calculates the difference between the updated sum of the row sums and the sum of the column sums. As a result, if the sum difference is 0, the row sum / column sum update unit 110 terminates the update of the row sum or the column sum here. In this case, since the total difference is 2, the process proceeds to the next update calculation.
That is, the row sum 83 of the seventh row which is the maximum value among the row sums which have not been updated is selected, and the correction value 1 is added. As a result, 7
The sum of the rows is 84, and the total sum of the rows is 2343. FIG. 17 shows the updated row sum after the correction value addition.

Here, again, the sum difference calculating means 80 calculates the difference between the updated sum of the row sums and the sum of the column sums. At this time, since the total sum difference is still 1, the row sum / column sum update unit 110 proceeds to the next update calculation. That is, the row sum 49 of the twelfth row, which is the maximum value among the row sums that have not been updated, is selected, and the correction value 1 is added. By this calculation, the row sum of the twelfth row becomes 50, and the sum of the row sums becomes 2344. FIG. 18 shows the updated row sum after the correction value addition.

Next, again, the sum difference calculating means 80
The total difference between the updated row sum and the column sum is calculated. Here, since the sum difference has become 0, the row sum / column sum update means 1
10 ends the update calculation. After correcting the sum of the row sum and the sum of the column sum in this way, O
The D table estimating means 60 estimates the OD table based on the row sum / column sum corrected by the row sum / column sum correcting means 70 and the prior OD table generated by the prior OD table generating means 40.

As described above, according to the third embodiment, even when the sum of the row sums and the sum of the column sums necessary for the OD table estimation do not match, the sums of the two sums match. After the row sum or the column sum is corrected, the OD table can be estimated.

Next, a fourth embodiment of the present invention will be described. FIG. 19 is a block diagram of an OD table estimating device for a lift according to the fourth embodiment of the present invention. This fourth
The OD table estimating device 1 for a lift according to the embodiment of the present invention is different from the first embodiment shown in FIG. 1 in that the operation information of the elevator stored in the operation information storage means 20 is divided into a plurality according to a predetermined standard. The operation information dividing means 120 to be divided, and the estimated OD table totaling means 13 for totalizing the results of the OD table estimation performed by the OD table estimating means 60 for each of the divided operation information.
This is a configuration in which 0 is added.

The row sum / column sum generation means 30 and the prior OD table generation means 40 execute the row sum / column sum and the prior experiment for each division unit on the basis of each operation information divided by the operation information division means 120. OD tables are sequentially generated, and OD table estimating means 60 is generated.
Are the row sum / column sum generation means 30 and the prior OD table generation means 4
With the row sum / column sum generated by 0 and the prior OD table as inputs,
OD table estimation is sequentially performed for each division unit.

The operation information of the elevator is measured by the traffic measuring means 10, and the operation information storing means 20 of the measured operation information is provided.
Is stored in the same manner as in the first embodiment. It is assumed that the knowledge stored in the knowledge storage means 50 is the same as the knowledge stored in the knowledge storage means 50 in the first embodiment. FIG. 20 shows an example of the operation information of the elevator stored in the operation information storage means 20 according to the fourth embodiment.

The operation information dividing means 120 divides the operation information of the elevator stored in the operation information storage means 10 into a plurality of pieces according to a predetermined standard. In the fourth embodiment,
The operation information is divided into one unit while the traveling direction of the elevator is the same. FIG. 21 shows operation information divided according to this criterion. In this example, the original operation information of FIG. 20 is divided into three.

Here, the information at the time of stopping at the fifth floor written on the fifth line in FIG. 20 is divided into the fifth line of the division unit 1 and the first line of the division unit 2 in FIG. This means that the passenger who arrived on the 5th floor and moved in the UP direction got off the basket and the load became 0 kg, and the direction was treated as operation information during the UP, and from the point where the load became 0 kg, DOW
This is because the direction from which the passenger traveling in the N direction gets on the car is handled as operation information during the DOWN period. For the same reason, the information at the time of stopping at the first floor written on the ninth line in FIG. 20 is divided into the fifth line of the division unit 2 and the first line of the division unit 3 in FIG. By dividing the operation information in this way, the division unit 1 and the division unit 3 divide the operation information while the traveling direction is UP into the division unit 2
Indicates the operation information while the traveling direction is DOWN.

Here, the method of dividing the operation information is not limited to the above-mentioned method, and the operation information is divided into two according to the UP and DOWN directions, and the operation until the load returns from the state of 0 to the state of 0 again. It can also be divided as one unit.

Next, OD table estimation is sequentially performed on each piece of the operation information divided by the operation information dividing means 120 as follows. The row sum / column sum generation means 30 is the knowledge storage means 5
Operation information dividing means 1 while referring to the knowledge stored in
OD based on one unit of operation information divided by 20
Generates row sum and column sum necessary for performing table estimation. The prior OD table generating means 40 is necessary for performing the OD table estimation based on the operation information for one unit divided by the operation information dividing means 120 while referring to the knowledge stored in the knowledge storage means 50. Generate a prior OD table.

For division unit 1, row sum / column sum generation means 3
FIG. 22 shows 0, the row sum / column sum generated by the prior OD table generation means 40, and the prior OD table. Then, the OD table estimating means 6
0 is the row sum / column sum generated by the row sum / column sum generating means 30 and the prior O generated by the prior OD table generating means 40
Using a predetermined optimization method from the D table, an OD table that satisfies the constraint condition of the row sum and the column sum and is closest to the prior OD table is estimated. Estimation result when the OD table estimating means 60 performs the OD table estimation by using the calculation method of the same applicant's patent application No. 8-27432 "OD table integer estimating apparatus" for the division unit 1. Is shown in FIG.

The estimated OD table totalizing means 130 sequentially adds the estimated OD tables estimated by the OD table
Aggregate the table. However, the first time the OD table estimating means 60
Simply stores the estimated OD table estimated by. FIG. 2 shows the first counting result of the estimated OD table by the estimated OD table counting means 130.
It is shown in FIG.

This series of operations is performed by the operation information dividing means 12.
The process is repeated until the OD table estimation for all the operation information divided by 0 is completed. That is, next, the division unit 2
To the sum of rows and columns and the prior O
The generation of the D table, the estimation of the OD table, and the addition and storage of the estimated OD table are performed. For the division unit 2, the row sum / column sum and the prior O generated by the row sum / column sum generating means 30 and the prior OD table generating means 40
FIG. 25 shows the D table, and FIG. 26 shows the results of the OD table estimation performed by the OD table estimating means 60. FIG. 27 shows the result of summing up the estimated OD table by the estimated OD table summing means 130.

The same procedure is repeated for division unit 3. For the division unit 3, the row sum / column sum generation means 30
FIG. 28 shows the row sum / column sum and the prior OD table generated by the prior OD table generating means 40 and the O
FIG. 29 shows the result of the D-table estimation. Estimated OD table totaling means 1
FIG. 30 shows a totaling result of the estimated OD table obtained by using No. 30. Thus, the estimation of the OD tables and the summation of the OD tables for all the divided units are completed, and the estimated OD tables of the entire estimation target are obtained.

For comparison, the OD table estimating device 1 of the elevator according to the first embodiment of the present invention estimates the OD table without dividing the operation information shown in FIG. FIG. 31 shows the column sum and the prior OD table, and FIG. 32 shows the OD table estimation results. O according to the fourth embodiment shown in FIG.
In the D table estimation result, x21 = 3, x31 = 0, and x32 = 0, whereas in the OD table estimation result according to the first embodiment shown in FIG. 32, x21 = 2, x31 = 1, x32 = 1. By the way, from the operation information of division unit 2,
It is clear that the number of passengers from the second floor at the time of DOWN (that is, the number of passengers who moved from the second floor to the first floor × 21) is 3. Also, the number of passengers from the third floor at the time of DOWN (that is, the number of passengers who moved from the third floor to the second or first floor x32,
It is also clear that x31) is 0. Therefore, the fourth
The OD table estimation obtained by dividing the operation information according to the embodiment of
It can be seen that the estimation accuracy is improved as compared with the case without division.

According to the fourth embodiment, since the operation information is divided and the OD table is estimated, and the results are totaled, higher estimation accuracy is achieved than when the OD table estimation is performed collectively. OD table estimation can be realized.

Next, a fifth embodiment of the present invention will be described. FIG. 33 is a block diagram showing a configuration of an OD table estimating device for a lift according to the fifth embodiment of the present invention. The elevator OD table estimating device 4 according to the fifth embodiment includes, as components of the first embodiment of the present invention, an image of a hall (a landing) of an elevator, and the image is analyzed. In this configuration, a hall number detecting means 140 for detecting the number of customers in the hall and calculating the number of people getting on and off is added.

The number-of-holes detecting means 140 includes a hall photographing means 150 for photographing the hall, an image analyzing means 160 for detecting the number of passengers in the hall by analyzing the image of the hall photographed by the hall photographing means 150, And the number of passengers getting on and off calculating means 170 for calculating the number of passengers getting on and off based on the number of halls detected by the analyzing means 160. Then, the row sum / column sum generation unit 30 converts the row sum / column sum generated from the operation information into the hall number detection unit 14 for the floor for which the number of boarding / exiting passengers has been calculated by the hall number detection unit 140.
The sum of rows and columns is replaced by the number of passengers calculated by 0.

In the fifth embodiment, the operation information of the elevator is measured by the traffic measurement means 10 in the fifth embodiment, the measured operation information is stored in the operation information storage means 20, and the row sum / column sum and the prior OD table are stored. The storage of the generated knowledge in the knowledge storage means 50 is performed in the same manner as in the first embodiment.

The hall photographing means 150 is provided on all or a part of the stop floor. Before and after the car arrives at the floor on which the hall photographing means 150 is provided, the hall photographing means 150 photographs a video of the hall (the landing of the elevator). The image analyzing means 160 analyzes the image of the hall taken by the hall photographing means 150, so that the number of halls (the number of passengers in the hall) before and after the arrival of the basket.
Is detected. The number of passengers calculating board 170 calculates the number of passengers based on the number of halls detected by the image analyzer 160.

The method of calculating the number of people getting on and off in the fifth embodiment is as follows. In the case of the lowest floor or the top floor, all the passengers waiting for the arrival of the car in the hall will board the arriving car. This is because, in the case of the lowest floor or the top floor, the traveling direction of the arriving car is one direction (UP for the lowest floor, DOWN for the top floor). Therefore, the number of halls before arrival at the car is defined as the number of riders on that floor, and the number of halls after departure of the basket is defined as the number of people getting off at that floor. In the case of the middle floor, not all passengers who have arrived in the hall will get into the arrived basket. Therefore, if the number of halls before the arrival at the car is 0, the number of halls after the departure of the car is taken as the number of people descending on that floor. If the number of halls is zero after departure from the car, the number of halls before arrival at the car is taken as the number of riders on that floor. In other cases, the number of passengers cannot be calculated. In this way, the number of passengers calculating means 1
70 calculates the number of people getting on and off the floor on which the hall photographing means 150 is provided.

The row sum / column sum generation means 30 and the a priori OD table generation means 40 refer to the knowledge in the knowledge storage means 50 and generate the row sum / column sum and the a priori OD table generation means 40 in the same manner as in the first embodiment. Generate a prior OD table. However, the row sum / column sum generation means 30
Means for detecting the number of halls 1 when generating the row sum / column sum
For floors for which the number of halls could be calculated by 40, the row sum generated from the operation information is replaced with the number of passengers calculated by the hall number detection means 140, and the column sum generated from the operation information is calculated by the hall number detection means 140 It is replaced by the number of people who got off and the sum of rows and columns is used. After the row sum / column sum and the prior OD table are generated in this way, the OD table estimating means 60 performs the OD table estimation in the same manner as in the first embodiment.

According to the fifth embodiment, when generating the row sum / column sum necessary for OD table estimation and the prior OD table,
It is possible to use not only the operation information of elevators but also the information of the number of people getting on and off the vehicle obtained by analyzing the image of the hall (platform), so that OD using row sum and column sum more reliable Table estimation can be realized.

Next, a sixth embodiment of the present invention will be described. FIG. 34 is a block diagram showing the configuration of an OD table estimating device for a lift according to the sixth embodiment of the present invention. The OD table estimating device 5 for a lift according to the sixth embodiment includes a passenger input / output device for inputting the passengers obtained by means other than the traffic measuring device 10 to the components of the first embodiment. 180 is added.

The row sum / column sum generation means 30 inputs the row sum / column sum generated from the operation information from the passenger input / output means 180 with respect to the floor to which the number of passengers has been input from the passenger input / output means 180. Gy 和 wa
Column sum.

(Operation of the Sixth Embodiment) The operation information of the elevator is measured by the traffic measuring means 10 in the sixth embodiment, the measured operation information is stored in the operation information storing means 20, and the sum of The storage of the column sum and the generation knowledge of the prior OD table in the knowledge storage means 50 is performed in the same manner as in the first embodiment.

The number of passengers getting on and off is input to the passenger input / output unit 180 by means other than the traffic measuring means 10. In estimating the OD table of elevators, in order to obtain a more accurate estimate, carry out a survey of the number of boarding and dismounting by hand only on all or specific floors, and record the time stamp at the time of going to work or leaving the company The number of people getting on and off each floor or a specific floor may be calculated on the basis of the information. In such a case, the number of passengers obtained by a method other than the method of calculating the number of passengers based on the operation information as described above is input by the passenger input / output device 180.

The row sum / column sum generation means 30 and the prior OD table generation means 40 refer to the knowledge in the knowledge storage means 50 and generate the row sum / column sum and the prior art OD table generation means 40 in the same manner as in the first embodiment. Generate a prior OD table. However, the row sum / column sum generation means 30
Replaces the row sum generated from the operation information with the number of passengers manually input from the passenger input / output unit 180, and replaces the column sum generated from the operation information with only the floor where the number of passengers is input to the passenger input means 180. The sum of rows and columns is generated by replacing the number of descendants input from the number input means 180.
After the row sum / column sum and the prior OD table are generated in this way, the OD table estimating means 60 performs the OD table estimation in the same manner as in the first embodiment.

According to the sixth embodiment, when generating the row sum / column sum required for OD table estimation and the prior OD table,
It is also possible to use information of the number of passengers obtained and obtained using information other than the operation information of the elevator, and therefore, it is possible to realize an OD table estimation using a more reliable row sum and column sum.

[0111]

As can be seen from the above description, according to the elevator OD table estimating apparatus of the present invention, the row sum / column sum necessary for the OD table estimation and the prior OD table are automatically obtained from the operation information of the elevator. Can be generated dynamically. Also, when generating the row sum / column sum and the prior OD table from the operation information, if the generation results of the row sum / column sum and the prior OD table differ depending on the knowledge used, the inconsistency is resolved. It is possible to uniquely determine the generation result. Further, when generating the row sum / column sum required for the estimation, it is also possible to use the row sum / column sum generated based on information other than the operation information.

If there is a contradiction in the row sum / column sum generated based on the operation information, the OD table can be estimated after correcting the contradiction. Further, by dividing the operation information and estimating the OD table and summing up the results, it is possible to realize higher estimation accuracy than in the case where the OD table estimation is performed collectively. Thereby, it is possible to automatically realize the OD table estimation of the elevator with higher accuracy than before.

[Brief description of the drawings]

FIG. 1 is a block diagram of an OD table estimating device for an elevator according to a first embodiment of the present invention.

FIG. 2 is an explanatory diagram of operation information of an elevator stored in an operation information storage unit according to the first embodiment of the present invention.

FIG. 3 is an explanatory diagram of row sum / column sum and prior OD table generation knowledge stored in a knowledge storage unit in the first embodiment of the present invention.

FIG. 4 is an explanatory diagram of a row sum / column sum generated by a row sum / column sum generation unit according to the first embodiment of the present invention.

FIG. 5 is an explanatory diagram of a prior OD table initialized by a prior OD table generation unit according to the first embodiment of the present invention.

6 is an explanatory diagram of a prior OD table obtained by updating the prior OD table of FIG. 5 with reference to the knowledge g1 of FIG. 3;

7 is an explanatory diagram of a prior OD table obtained by updating the prior OD table of FIG. 6 with reference to the knowledge g2 of FIG. 3;

8 is an explanatory diagram of a prior OD table obtained by updating the prior OD table of FIG. 7 with reference to the knowledge g3 of FIG. 3;

FIG. 9 is an explanation of a row sum / column sum generated by a row sum / column sum generating unit and a prior OD table generated by a prior OD table generating unit according to the first embodiment of the present invention; FIG.

FIG. 10 is an explanatory diagram of an OD table estimation result by an OD table estimation unit according to the first embodiment of the present invention.

FIG. 11 is an explanatory diagram of generated knowledge of a row sum and a column sum stored in a knowledge storage unit according to the second embodiment of the present invention.

FIG. 12 is an explanatory diagram of operation information of an elevator stored in operation information storage means according to the second embodiment of the present invention.

FIG. 13 is a block configuration diagram of an OD table estimating device for a lift according to a third embodiment of the present invention.

FIG. 14 is a diagram illustrating a sum of rows and columns generated by a sum of rows and columns generation unit and a priori O according to the third embodiment of the present invention;
It is explanatory drawing of Table D.

FIG. 15 is an explanatory diagram of a calculation result of a correction value calculated by a correction value calculation unit of a row sum / column sum correction unit according to the third embodiment of the present invention.

FIG. 16 is an explanatory diagram of a row sum after correction by a first update by a row sum / column sum update unit according to the third embodiment of the present invention.

FIG. 17 is an explanatory diagram of a row sum after correction by a second update by a row sum / column sum update unit according to the third embodiment of the present invention.

FIG. 18 is an explanatory diagram of a row sum after correction by a third update by a row sum / column sum update unit according to the third embodiment of the present invention.

FIG. 19 is a block diagram of an OD table estimating device for a lift according to a fourth embodiment of the present invention.

FIG. 20 is an explanatory diagram of operation information of an elevator stored in operation information storage means according to the fourth embodiment of the present invention.

FIG. 21 is an explanatory diagram of operation information divided by operation information dividing means according to the fourth embodiment of the present invention.

FIG. 22 is an explanatory diagram of a row sum / column sum of a division unit 1 of the divided operation information shown in FIG. 21 and a prior OD table.

FIG. 23 is an explanatory diagram of an OD table estimation result of division unit 1 by an OD table estimation unit in the fourth embodiment.

FIG. 24 is an explanatory diagram of the first counting result of the estimated OD table by the estimated OD table counting means in the fourth embodiment of the present invention.

FIG. 25 is an explanatory diagram of the row sum / column sum of the division unit 2 of the divided operation information shown in FIG. 21 and the prior OD table.

FIG. 26 is an explanatory diagram of an OD table estimation result of a division unit 2 by an OD table estimation unit according to the fourth embodiment.

FIG. 27 is an explanatory diagram of a second counting result of the estimated OD table by the estimated OD table counting unit in the fourth embodiment of the present invention.

FIG. 28 is an explanatory diagram of the row sum / column sum of the division unit 3 of the divided operation information shown in FIG. 21 and the prior OD table.

FIG. 29 is an explanatory diagram of an OD table estimation result of the division unit 3 by the OD table estimation unit in the fourth embodiment.

FIG. 30 is an explanatory diagram of a third counting result of the estimated OD table by the estimated OD table counting unit in the fourth embodiment of the present invention.

FIG. 31 is an explanatory diagram of a row sum / column sum and a priori OD table when the operation information shown in FIG. 20 is not divided;

FIG. 32 is an explanatory diagram of an OD table estimation result when the operation information shown in FIG. 20 is not divided.

FIG. 33 is a block diagram showing a configuration of an OD table estimating device for a lift according to a fifth embodiment of the present invention.

FIG. 34 is a block diagram of an OD table estimating device for an elevator according to a sixth embodiment of the present invention.

FIG. 35 is an explanatory diagram showing the concept of an OD table.

[Explanation of symbols]

 1 OD table estimation means 10 Traffic measurement means 20 Operation information storage means 30 Row sum / column sum generation means 40 Prior OD table generation means 50 Knowledge storage means 60 OD table estimation means 70 Row sum / column sum correction means 80 Sum difference calculation Means 90 Correction target selecting means 100 Correction value calculating means 110 Row sum / column sum updating means 120 Operation information dividing means 130 Estimated OD table totaling means 140 Hole number detecting means 150 Hole photographing means 160 Image analyzing means 170 Passenger getting on / off calculating means 180 Getting on / off Number input method

 ──────────────────────────────────────────────────の Continuing on the front page (72) Inventor Toshiaki Matsumoto 1 Toshiba-cho, Fuchu-shi, Tokyo Inside the Fuchu plant of Toshiba Corporation

Claims (11)

[Claims] 1. A traffic measuring means for measuring operation information of an elevator, an operation information storage means for storing operation information of the elevator measured by the traffic measuring means, and an operation information of the elevator stored in the operation information storage means. Knowledge storage means for storing the row sum / column sum for the OD table to be estimated from the OD table and the knowledge used when generating the a priori OD table; and storing the operation information using the knowledge stored in the knowledge storage means. A row sum / column sum generating means for generating a row sum / column sum for an OD table to be estimated from the operation information of the elevator stored in the means, and the operation information storage using the knowledge stored in the knowledge storage means A prior OD table generating means for generating a prior OD table for an OD table to be estimated from the operation information of the elevator stored in the means;
OD table estimating means that satisfies the constraint condition of the row sum / column sum generated by the row sum / column sum generating means and estimates the OD table closest to the prior OD table generated by the prior OD table generating means And an OD table estimating device for a lift. 2. The knowledge storage device according to claim 1, wherein said knowledge storage means stores the knowledge to be stored with a priority added thereto, and said row sum / column sum generation means and said prior OD table generation means. When generating a row sum / column sum and a priori OD table, if data generation based on different knowledge in the knowledge storage means is inconsistent, the data generation result based on the high priority knowledge An OD table estimating apparatus for an elevator, wherein a row sum, a column sum, and a prior OD table are generated by employing the above. 3. The invention according to claim 1, further comprising hall number detection means for detecting the number of passengers in the hall of the elevator and calculating the number of passengers in and out, wherein the row sum / column sum generation means comprises:
Regarding the floor for which the number of boarding passengers can be calculated by the hall number detecting means, the row sum / column sum generated from the operation information is replaced with the passenger number calculated by the hall number detecting means to obtain a row sum / column sum. Elevator OD characterized by
Table estimation device. 4. The invention as set forth in claim 1, further comprising: a boarding / leaving person input means for inputting the number of people getting on and off the hall of the elevator; Regarding the floor where the number of people is input, the sum of rows and columns generated from the operation information is replaced with the number of people getting on and off the passengers input from the means for inputting and leaving passengers, and the sum of rows and columns is used as the sum of rows and columns. Table estimation device. 5. The sum of row sums related to the row sum / column sum generated by the row sum / column sum generation means based on the operation information of the elevator stored in the operation information storage means according to the invention of claim 1. When the sum of the row sum and the sum of the column sums do not match, row sum / column sum correction means for correcting the row sum / column sum so that the sum of the row sums and the sum of the column sums are provided. OD table estimation based on the row sum / column sum corrected by the row sum / column sum correction means and the prior OD table generated by the prior OD table generation means.
D-table estimator. 6. The invention according to claim 5, wherein the row sum / column sum correction means calculates a difference between the sum of the row sums generated by the row sum / column sum generation means and the sum of the column sums. A sum difference calculation unit, a correction target selection unit that selects which of a row sum and a column sum is to be corrected, and a row sum or a column sum that is a correction target selected by the correction target selection unit. Correction value calculating means for calculating a correction value that needs to be added or subtracted in order to eliminate the sum total difference, and selecting elements one by one from the row sum or the column sum of the correction target in descending order of value, and calculating the row sum. Row sum / column sum update for updating the value of the selected element by adding or subtracting the correction value calculated by the correction value calculating means to or from the value of the selected element until the difference between the total sum and the sum of the column sums disappears. Means for estimating an OD table of a lift. 7. The invention according to claim 6, wherein the correction target selecting means includes: “always select a row sum as a correction target”; “always select a column sum as a correction target”; If the sum of the row sums and column sums is even, the sum of the row sums and column sums is even. If the sum is larger, the odd sum is the smaller sum,
Select as a correction target '' or `` Select the row with the sum total difference between the row sum and the column sum, if the odd number is the larger sum, and if the even sum is the smaller sum, select the row with the smaller sum as the correction target. '' An OD table estimating device for a lift, which selects which of a sum and a column sum is to be corrected. 8. The operation information dividing means according to claim 1, wherein the operation information dividing means divides the operation information of the elevator stored in the operation information storing means into a plurality of parts according to a predetermined standard. OD table estimating means for estimating the respective OD table estimating means for each piece of operation information provided, and providing an estimated OD table totaling means, wherein the row sum / column sum generating means and the prior OD table generating means, A row sum / column sum and a priori OD for each division unit are sequentially generated based on each piece of the operation information divided by the operation information dividing means, and the OD table estimating means includes: the row sum / column sum generating means; Test OD
An OD table estimating device for a lift, which sequentially performs OD table estimation for each division unit based on the row sum / column sum generated by the table generating means and the prior OD table. 9. The invention according to claim 8, wherein the operation information dividing unit divides the operation information of the elevator stored in the operation information storage unit into two according to the UP and DOWN directions of the elevator. An OD table estimating device for a lift. 10. The invention according to claim 8, wherein the operation information dividing means divides the operation information of the elevator stored in the operation information storage means into one unit while the traveling direction is the same. OD table estimating device for elevators. 11. The invention according to claim 8, wherein the operation information dividing unit converts the operation information of the elevator stored in the operation information storage unit from a state where the load is 0 to a state where the load returns to the state of 0 again. An OD table estimating device for an elevator, which is divided as one unit.