BACKGROUND OF THE INVENTION
[0001] The present invention relates to an elevator group management system and a control
method therefor, and more particularly, to an elevator group management system and
a control method therefor for improving system performance evaluations and elevator
allocation control responsive to hall calls.
[0002] An elevator group management system provides an efficient operation service for users
by handling a plurality of elevator cages in one unit. Specifically, a plurality of
elevator cages (generally ranging from three to eight) are managed in one group, such
that an appropriate cage is selected from among this group in response to a new hall
call generated at a certain floor to allocate the hall call to that cage.
[0003] A current group management system is based on allocation control that relies on an
evaluation function based on a forecasted waiting time. For example, when a new hall
call is generated, the hall call is allocated to a cage which minimizes a forecasted
waiting time of a hall call serviced by each cage, a cage which minimizes a maximum
waiting time, or a cage which minimizes an average waiting time. This allocation control
based on the forecasted waiting time is a basic scheme employed in group call control
of every elevator manufacturer, but has the following two problems.
- 1) The allocation control offers an optimal cage allocation for previously generated
hall calls and does not sufficiently taken into consideration the influence of hall
calls which can be generated in the future.
- 2) A forecasted waiting time is indexed for allocation of a cage, without taking into
consideration the positional relationship among respective cages.
[0004] A variety of control schemes have been so far proposed in order to solve such problems
of the allocation scheme based on a forecasted waiting time. Their basic concepts
can be summarized into control intended to move respective elevator cages at equal
time intervals. Supposing that respective elevator cages are not even in position,
i.e., when there is a longer time interval between certain two cages, if a new hall
call is generated at a floor between the cages, the call is likely to suffer from
a long waiting time. It has been traditionally known that long waiting times can be
restrained if respective cages can be disposed at equal time intervals. The following
conventional control schemes are intended to the disposition of cages at equal time
intervals.
- 1) Representation of Interval between Cages in Coefficient (JP-B-7-12890)
An allocation evaluation function Φk is represented by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0001)
where Tk indicates a forecasted time of arrival of a K-th call at a floor at which
a new hall call was generated, and αk indicates a coefficient, the value of which
is determined from intervals between cages. Tk corresponds to a forecasted waiting
time index, and is intended to adjust a forecasted waiting time in accordance with
the intervals for evaluation using the product of the cage interval index and forecasted
waiting time.
- 2) Allocation Evaluation Control which Takes Temporal Equal Interval State into Index
(JP-B-7-72059) :
The position of each cage is forecasted at a future time point to predict time intervals
between the respective cages at that time point. An allocation limit evaluation value
is calculated from the forecasted cage intervals to control the allocation in such
a manner that cages are partially allocated to a particular floor range. As a result,
JP-B-7-72059 is intended to bring the intervals between the respective cages to an equal time
interval.
- 3) Equal Internal Preference Zone Control (JP-A-1-226676):
Floors serviced by cages are classified into a preferential zone and a limited zone,
and an allocation evaluation value is manipulated such that a cage is more likely
to be allocated when a new hall call is generated in the preferential zone, and is
less likely to be allocated when it is in the limited zone. In this way, JP-A-1-226676 is intended to bring the intervals between the respective cages to an equal time
interval.
- 4) Temporally Equal Interval Allocation Zone Control (JP-A-7-61722):
Like the prior art 3) described above, floors serviced by cages are classified into
a preferential zone and a limited zone, and an allocation evaluation value is manipulated
such that a cage is more likely to be allocated when a new hall call is generated
in the preferential zone, and is less likely to be allocated when it is in the limited
zone. In this way, JP-A-7-61722 is intended to bring the intervals between the respective cages to an equal time
interval.
- 5) Allocation Scheme Based on Position Evaluation Value (JP-A-2000-118890):
This scheme calculates a position evaluation value for preventing respective cages
from partially concentrating in position, and determines the allocation to a hall
call based on an allocation evaluation value which takes into account the position
evaluation value. This position evaluation value is calculated on the basis of a relationship
between an absolute position of a car and an average value of absolute positions of
the remaining cars when a hall call is generated. This scheme is also intended to
bring the intervals between the respective cages to an equal time interval.
- 6) Evaluation of Evenness in Forecasted Position (JP-A-8-175769):
A forecasted position of each cage after the lapse of a predetermined time is calculated
to select one which is most evenly spaced from among the forecasted positions, and
a cage corresponding to this forecasted position is allocated to a new hall call.
- 7) "Method of Calculating Forecasted Time of Arrival Using Dynamic Planning Method (2003
Institute of Electrical Engineers of Japan, Electronics, Information and Systems Society
Conference, GS-18-3, pp.1099-1102 (whole)):
An approach is disclosed for estimating a floor at which a cage call is generated
through n unserved ad-hoc call, using a dynamic planning method in order to accurately
finding a forecasted waiting time.
JP-B-7-72059 described above has a key factor in predicting the position of each cage in the future
to determine the allocation from time intervals between respective cages at that time.
However, this method simply evaluates the spatial position for each cage at a certain
time point (sometimes at certain time points) in the future, and lacks for information
for analyzing the contents of the evaluation. Specifically, an analysis on the cause
of the allocation evaluation must involve individually analyzing information on the
spatial positions of cages at a certain time point, giving rise to difficulties in
macroscopic analysis. Also, since the position is individually forecasted on a stage-by-stage
basis, another problem experienced herein is a low forecast accuracy. Particularly,
in a building which has a long interval between floors, the forecast accuracy affects
the control performance.
[0007] Generally, the performance of an elevator group management system is evaluated in
regard to a short average waiting time, a low probability of a long waiting time after
a call, and the like. However, difficulties are often experienced in making detailed
evaluations on the system under a variety of varying traffic demands within a building
due to unknown reasons for which the control performance differs.
[0008] It is a first object of the present invention to provide a system which supports
evaluations on system control performance in an elevator group management system.
[0009] Also, in the prior art techniques listed above, an important key for determining
the control performance is balanced evaluations on a waiting time to a hall call and
on a positional relationship (intervals) among respective cages. As has been previously
described, the evaluation on a waiting time to a hall call corresponds to an evaluation
for a hall call which has been actually made (hereinafter called the "actual call"),
while the evaluation on the intervals between respective cages corresponds to a hall
call which can be made in the future (hereinafter called the "future call"). Therefore,
the aforementioned balancing involves balancing the actual call with the future call.
[0010] The following three general classifications can result from a review on how the above
listed prior art techniques accomplish the balanced evaluations. (A) There is no balancing
means. (B) Two evaluations are weighted for balancing. However, there is no means
for adjusting the weighting values. (C) Two evaluations are weighted for balancing.
Weighting values are determined by repeatedly simulating the group management control
for a traffic flow in a building. Specifically, Prior Art Techniques 1) and 6) fall
under the classification (A); Prior Art Techniques 2), 4), and 5) fall under the classification
(B); and Prior Art Technique (3) falls under the classification (C).
[0011] For a reduction in waiting times of all users, balancing through the weighting of
the actual call and future call is indispensable, and the weighting must be further
adjusted in accordance with elevator used situations. Therefore, Prior Art Technique
(3) which falls under the classification (C) alone satisfies this condition. However,
this method must repeatedly execute the simulation to find weights suitable for a
particular traffic flow, and therefore takes a long time until appropriate weights
are found. The weights can be set with a delay because the traffic flow in a building
is a flow of persons and varies at all times. Also, in a transient state in which
appropriate weights have not been found, a problem arises in how weights should be
set in order to guarantee the performance. Further, immediately after the introduction
of a group management, in the event of a replacement of a tenant in a building, on
the occurrence of a special event, and the like, a long time is required for setting
weights due to the lack of accumulated past traffic flows, giving rise to a challenge
of how the weights should be set in the so far transient state.
[0012] It is a second object of the present invention to promptly set weights for balancing
an evaluation on a waiting time with an evaluation on a positional relationship (for
example, intervals) between respective elevator cages to appropriate weights corresponding
to variations in used situations for an evaluation on the allocation of a new hall
call.
[0013] Also, in the prior art techniques described above, the allocation control for allocating
a hall call to an elevator cannot always appropriately control the intervals for a
varying traffic flow in a building to possibly cause a long average waiting time.
[0014] It is a third object of the present invention to provide an elevator group management
system and a control method therefor which comprises hall call allocation control
capable of accomplishing appropriate interval control for a varying traffic flow in
a building to reduce an average waiting time.
SUMMARY OF THE INVENTION
(Means for Achieving First Object)
[0015] To achieve the first object of the present invention, one preferred embodiment of
the present invention is characterized by comprising forecasted trajectory creating
means for creating a forecasted trajectory indicative of movements of a forecasted
position of each elevator on a time axis for a predetermined period from a current
time point to the near future.
(Means for Achieving Second Object)
[0016] To achieve the second object of the present invention, a preferred embodiment of
the present invention provides an elevator group management system for managing a
plurality of elevators which service a plurality of floors. The system calculates
a plurality of evaluation values for a generated hall call, calculates a general evaluation
value by weighting and adding the plurality of evaluation values, calculates the value
of a weight used by the general evaluation value calculating means, allocates a hall
call to an elevator in accordance with the general evaluation value by calculating
the value of the weight based on a function which continuously changes an output value
in response to a change in an input.
[0017] Stated another way, the value of the weight is calculated on the basis of a function
which is applied with a real number which continuously changes the value.
[0018] Also, in a preferred embodiment of the present invention, weight calculating means
calculates the value of the weight by a linear function or a function of a plurality
of orders or a polynomial function.
[0019] Further, in a preferred embodiment of the present invention, the input of the function
is a value related to the number of generated hall calls.
(Means for Achieving Third Object)
[0020] For an evaluation for a positional relationship between respective cages, for example,
an interval, it is important to evaluate the interval at which time point, which has
been found to largely affects the performance of the group management system. For
example, when a cage interval is evaluated, for example, at a immediately near time
point, a cage can pass another at a later time, resulting in an inversion of the cage
interval therebetween. On the other hand, when a cage positional relationship (interval)
is evaluated at an extremely far future time point, a large number of calls can be
generated after the evaluation, causing a forecasted interval to largely deviate.
The aforementioned prior art techniques do not specifically disclose an important
time point at which the cage interval should be evaluated, so that the evaluated cage
interval can have a large error, possibly failing to demonstrate sufficient group
management control performance.
[0021] Accordingly, to achieve the third object of the present invention, a preferred embodiment
of the present invention provides an elevator group management system which forecasts
the position of each elevator, evaluates the positional relationship between the respective
cages from after a predetermined time from the forecasted position of each cage, and
allocates a hall call to an elevator in accordance with the evaluation value, where
the predetermined time is set in accordance with a situation of a generated hall call
and/or a cage call. In other wards, in interval evaluation time is set in accordance
with a call generation state.
[0022] Also, in a preferred embodiment of the present invention, the evaluation time for
a forecasted interval between the respective cars in the future is set in accordance
with the longest forecasted arrival time of all hall calls and cage calls.
[0023] Further, in a preferred embodiment of the present invention, the evaluation time
for the forecasted interval between the respective cages in the future is set in accordance
with a measured traffic flow in a building.
[0024] Specifically, it is contemplated to set the evaluation time for the forecasted interval
between the respective cages in the future at a forecasted arrival time of a call
having the longest forecasted arrival time in all hall calls and cage calls, or the
vicinity thereof, or one round time of each elevator.
[0025] According to the elevator group management system according to the preferred embodiment
for achieving the first object, the elevator group management control can be properly
evaluated from a forecasted trajectory of each elevator on the time axis. Also, from
this, it is possible to provide technical supports for the evaluation and improvements,
such as giving a suggestion to necessary improvements. For example, when there is
a large forecast error, it can be determined from the slope of the forecasted trajectory
whether or not this is due to an error in an estimation of a traffic demand, and the
like.
[0026] According to the preferred embodiment for achieving the second object of the present
invention, against an evaluation for allocating an elevator cage for new hall call,
an appropriate weight can be immediately set depending on changing situation as a
weight which balances an evaluation for waiting time and an evaluation for each elevator
cage interval. Especially, in case of soon after an introduction of a group control
system, a change of a tenant, or a generation of a special event and so on, an appropriate
weight can be immediately set even if there are few stocks of traffic flows of the
past.
[0027] Also, according to the preferred embodiment for achieving the third object of the
present invention, the positional relationship between the respective cages can be
evaluated at an appropriate time point in order to allocate an elevator to a hall
call. It is therefore possible to provide an elevator group management system and
a control method therefor which comprises hall call allocation control which accomplish
appropriate interval control and is capable of reducing an average waiting time.
[0028] Other objects and features according to the present invention will become apparent
from the following description of embodiments.
BRIEF DESCRIPTION OF THE DRAWINGS
[0029]
Fig. 1 is a control conceptual diagram of an elevator group management system according
to the present invention;
Fig. 2 is a control functional block diagram of an elevator group management system
according to one embodiment of the present invention;
Fig. 3 is a control processing flow diagram of the elevator group management system
according to one embodiment of the present invention;
Fig. 4 is a graph for describing a method of setting weighing coefficients according
to one embodiment of the present invention;
Fig. 5 is a conceptual diagram of an optimal solution search method for weighting
coefficients according to one embodiment of the present invention;
Fig. 6 is an explanatory diagram of how to think an exemplary traffic flow and weighting
in a building having six floors;
Fig. 7 is a diagram for describing an example of a weighting coefficient setting method
when an input is handled in a traffic flow;
Fig. 8 is a diagram for comparing one embodiment of the present invention with a conventional
weighting coefficient setting method;
Fig. 9 is a processing flow diagram of a weighting coefficient setting method according
to one embodiment of the present invention;
Fig. 10 is a processing flow diagram of an optimal solution search method for weighting
coefficients according to one embodiment of the present invention;
Fig. 11 is a diagram showing exemplary data within an input information storage unit
2 shown in Fig. 2;
Fig. 12 is a diagram illustrating in detail the configuration of a cage interval evaluation
value processing unit 4 shown in Fig. 2;
Fig. 13 is a processing flow diagram for setting an interval evaluation time tref;
Fig. 14 is an explanatory diagram of how to think the setting of an interval estimation
time according to one embodiment of the present invention;
Fig. 15 is a functional block diagram of a second embodiment of the interval evaluation
value processing unit which is substituted for the counterpart illustrated in Fig.
12;
Fig. 16 is a functional block diagram of a third embodiment of the interval evaluation
value processing unit which is substituted for the counterpart illustrated in Fig.
12;
Fig. 17 is a functional block diagram of a fourth embodiment of the interval evaluation
value processing unit which is substituted for the counterpart illustrated in Fig.
12;
Fig. 18 is a general processing flow diagram of a forecasted trajectory creation method
according to one embodiment of the present invention;
Fig. 19 is a processing flow diagram for creating an arrival forecasted time table
of a plurality of cycles according to one embodiment of the present invention;
Fig. 20 is a processing flow diagram of an arrival forecasted time table calculation
routine (FB04 in Fig. 19);
Fig. 21 is an explanatory diagram for a stop time, a stop probability, and a stop
time expected value table for each floor;
Fig. 22 is a diagram showing a specific example of the arrival forecasted time table
of a plurality of cycles using values shown in Fig. 21;
Fig. 23 is a diagram showing an example of the arrival forecasted time table eventually
crated in accordance with one embodiment of the present invention;
Fig. 24 is a forecasted position calculation conceptual diagram which is based on
a forecasted trajectory according to one embodiment of the present invention;
Fig. 25 is a processing flow diagram (No. 1) for creating a forecasted trajectory
table according to one embodiment of the present invention;
Fig. 26 is a processing flow diagram (No. 2) for creating the forecasted trajectory
table according to one embodiment of the present invention;
Fig. 27 is a flow diagram of a forecasted trajectory creation process without direction;
Fig. 28 is a diagram showing an exemplary forecasted trajectory which is created by
a forecasted trajectory creation method according to one embodiment of the present
invention;
Fig. 29 is an explanatory diagram of a forecasted trajectory, involving a waiting
time, which places importance on an inactive period;
Fig. 30 is a second example of the forecasted trajectory crated by the forecasted
trajectory creation method according to one embodiment of the present invention;
Fig. 31 is a third example of the forecasted trajectory crated by the forecasted trajectory
creation method according to one embodiment of the present invention;
Fig. 32 is a fourth example of the forecasted trajectory crated by the forecasted
trajectory creation method according to one embodiment of the present invention;
Fig. 33 is a fifth example of the forecasted trajectory crated by the forecasted trajectory
creation method according to one embodiment of the present invention;
Fig. 34 is sixth example of the forecasted trajectory crated by the forecasted trajectory
creation method according to one embodiment of the present invention;
Fig. 35 is a seventh example of the forecasted trajectory crated by the forecasted
trajectory creation method according to one embodiment of the present invention;
Fig. 36 is a processing flow diagram for calculating a forecasted interval value according
to one embodiment of the present invention;
Fig. 37 is an explanatory diagram for calculating a forecasted interval value from
a forecasted route according to one embodiment of the present invention;
Fig. 38 is an explanatory diagram of a process for calculating a forecasted interval
according to one embodiment of the present invention;
Fig. 39 is a diagram of an exemplary comparison of cage operation trajectories before
and after employment of one embodiment of the present invention;
Fig. 40 is a conceptual diagram of an example of target route control according to
one embodiment of the present invention;
Fig. 41 is an explanatory diagram of how a hall call is allocated to an elevator in
accordance with a target route;
Fig. 42 is a general explanatory diagram of a target route creation process according
to one embodiment of the present invention;
Fig. 43 is a diagram of exemplary route shapes before and after an adjustment according
to one embodiment of the present invention;
Fig. 44 is a functional block diagram of an exemplary target route creation unit according
to one embodiment of the present invention;
Fig. 45 is a control functional block diagram of an elevator group management system
according to a second embodiment of the present invention;
Fig. 46 is a graph of an example of a weighting coefficient calculation function used
by a weighting coefficient calculation unit 5 in Fig. 45;
Fig. 47 is a control functional block diagram of an elevator group management system
according to a third embodiment of the present invention;
Fig. 48 is a detailed functional block diagram of an interval evaluation value calculation
unit according to one embodiment of the present invention;
Fig. 49 is a diagram showing an example of screen output data displayed in accordance
with one embodiment of the present invention;
Fig. 50 is a diagram showing a second example of screen output data displayed in accordance
with another embodiment of the present invention;
Fig. 51 is a diagram showing a third example of screen output data displayed in accordance
with another embodiment of the present invention;
Fig. 52 is a processing flow diagram of a forecasted trajectory display method according
to one embodiment of the present invention; and
Fig. 53 is a processing flow diagram of a forecasted trajectory display method according
to another embodiment of the present invention.
DESCRIPTION OF THE INVENTION
[0030] In the following, embodiments of the present invention will be described with reference
to the accompanying drawings.
[0031] To begin with, the concept of control underlying an elevator group management system
in the present invention will be described with reference to Fig. 1. Figs. 1(a), 1(b),
1(c) are control conceptual diagrams of the elevator group management system according
to the present invention. The description will be begun with Fig. 1(a). Fig. 1(a)
represents a scenario immediately after a new hall call has been made, where a cage
is going to be allocated in response to the hall call. This Fig. 1(a) represents an
elevator operation diagram, where the horizontal axis represents the time, and the
vertical axis represents floor positions in a building. The time axis represents future
time beginning from the current time. In other words, this diagram represents an elevator
forecasted operation diagram in the future. The elevator comprises two cages, i.e.,
a first car and a second car. It can be seen from Fig. 1(a) that the first car is
located near the third floor and is moving upward at the current time. The second
car is located near the fifth floor and is moving upward. Forecasted trajectories
of the respective cages are represented by lines on the diagram. The two forecasted
trajectories are close to each other, from which it is understood that the two cages
are operated in bunch. Consider that a new hall call is made on the eighth floor for
an upward transportation in such a situation.
[0032] Fig. 1(b) represents a forecasted trajectory of each cage when the newly generated
hall call is preliminarily allocated to the first car. As seen in the forecasted trajectory
of the first car, the first car is stopped on the eighth floor for upward movement
in order to service the new hall call. As a result, the subsequent forecasted trajectories
of the first car and second car are spaced more from the previous state shown in Fig.
1(a). When this interval between the forecasted trajectories is evaluated using a
positional relation evaluation time tref after the lapse of a predetermined time period
from the current time, it can be clearly appreciated that the interval has extended
in Fig. 1(b), as compared with Fig. 1(a). A representative example of the positional
relationship between the respective cages is the interval, and in the following, the
positional relationship evaluation time tref is simply called the "interval evaluation
time tref."
[0033] Fig. 1(c) represents a forecasted trajectory of each cage when a newly generated
hall call is preliminary assigned to the second car. It can be seen from the forecasted
trajectory of the second car that the second car is stopped on the eighth floor for
upward movement in order to service the new hall call. As a result, the subsequent
forecasted trajectories of the first car and second car are spaced less than the previous
state of Fig. 1(a), to end up in a completely bunch operation state.
[0034] From a comparison between the intervals between the respective cages at the interval
evaluation time tref in the scenario of Fig. 1(b) where the new hall call is preliminarily
allocated to the first car, and in the scenario of Fig. 1(c) where the new hall call
is preliminarily allocated to the second car, it can be understood that the allocation
to the first car results in an approach to an equidistant state. It can therefore
be evaluated that the allocation to the first car is better in order to approach to
the equidistance state. Such a sequence of evaluation methods is the concept of group
management control according to one embodiment of the present invention. As a result
of such control, appropriate intervals can be maintained at all time to reduce an
unnecessary long waiting time. For this purpose, it is necessary to find a forecasted
trajectory of each elevator for a predetermined time interval from that time point.
Fig. 1 illustrates by the length of the horizontal axis in accordance with the necessity,
where the length of the predetermined time is set to a time longer than an average
periodic time of the elevator at that time point.
[0035] Fig. 2 is a control block diagram of the whole elevator group management system according
to one embodiment of the present invention. The operations of N elevator cars 32A,
32B, 32C, ... are controlled by associated elevator car control apparatuses 31A, 31B,
31C, ... and a group management control unit 1 totally controls these car control
apparatuses.
[0036] The group management control unit 1 performs the following processes. First, information
on a hall call button (41A, 41B) on each floor, and information on each of N elevator
car apparatuses 31A, 31B, 31C are stored in an input information storage unit 1. Here,
if a new hall call is generated, a waiting time evaluation value calculation unit
3 calculates a forecasted waiting time for each hall call, including previously generated
hall calls, using the information in the input information storage unit 1, and calculates
a waiting time evaluation value W based on this. An interval evaluation value calculation
unit 4 in turn forecasts a positional relationship between the respective elevator
cages in the future, as described in connection with Fig. 1, and calculates an interval
evaluation value E based on this. A weighting coefficient setting unit 8 sets a weighting
coefficient WT corresponding to a situation at a particular time point. A feature
in this embodiment lies in a method of setting this weighting coefficient, the detail
of which will be described later. A general evaluation value calculation unit 6 calculates
a general evaluation value Φ by deriving a weighting sum of the waiting time evaluation
time and interval evaluation time from the waiting time evaluation time, interval
evaluation time, and weighting coefficient. The general evaluation value Φ is represented,
for example, by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0002)
[0037] This general evaluation value is calculated for a scenario where each cage is preliminary
allocated to a new hall call. An allocated elevator determination unit 7 determines
a cage to be allocated which exhibits the highest evaluation in regard to the waiting
time and cage interval uniformity.
[0038] Here, a description will be given of the key to the weighting coefficient setting
method which is a feature of this embodiment. The setting of the weighting coefficient
in accordance with this embodiment is roughly composed of two methods. A first method
determines a current traffic flow, repeatedly executes a group management control
simulation based on the traffic flow, and finds the most appropriate value for the
weighting coefficient through a search. A second method forecasts the number of hall
calls which can be possibly generated, and finds a weighting coefficient setting range
and an initial value for setting. Particularly, the latter (second method) constitutes
the key to this embodiment.
[0039] In the following, the respective methods will be described in a specific manner.
First, in the first method, a traffic flow determination unit 20 determines a current
traffic flow from information in input information storage unit 2, and a weighting
coefficient optimal solution search unit 21 searches for the value of the weighting
coefficient most suitable for the traffic flow. Here, the search for the optimal solution
for the weighting coefficient is conducted by repeatedly executing the group management
control simulation under a traffic flow condition at a particular time. This group
management control simulation is executed in a simulation unit 22. The weighting coefficient
optimal solution search may be conducted on line or may be conducted off line (for
example, during the night). When executed off line, a main traffic flow (hereinafter
called the "traffic flow mode") of a building concerned has been previously extracted
to executes the group management control simulation off-line for this traffic flow
mode.
[0040] Next, in the second method, a hall call count calculation unit 10 calculates the
number of times hall calls are generated or an amount related to the number of times
hall calls are generated based on input information in the input information storage
unit 2. Then, a weighting coefficient initial value calculation unit 12 and a weighting
coefficient range calculation unit 11 calculate an initial value for the weighting
coefficient and a range (an upper limit value and a lower limit value), respectively,
based on the number of times hall calls are generated.
[0041] There are two flows for the calculated initial value for the weighting coefficient:
a flow to the weighting coefficient setting unit 8, and a flow to the weighting coefficient
optimal solution search unit 21. The initial value sent to the weighting coefficient
optimal solution search unit 21 is used as an initial value for a search (initial
value when a search is made in regard to the first traffic flow). The initial value
sent to the weighting coefficient setting unit 8 is set as a weighting coefficient
which is actually used when the weighting coefficient optimal solution search is not
converged for a traffic flow which is emerging at a particular time point, or when
a traffic flow emerging at a particular time point is completely the first traffic
flow.
[0042] Fig. 3 is a control processing flow diagram of the elevator group management system
according to the one embodiment of the present invention illustrated in Fig. 2. In
the following, the flow will be described with reference to Fig. 3.
[0043] It is first determined whether or not the weighting coefficient optimal solution
search should be made (ST001). This is processing performed when the weighting coefficient
search is made through an off-line simulation. For example, it is determined whether
or not the weighting coefficient optimal solution search should be made based on the
state of a load on a processing apparatus such as a microcomputer or a personal computer,
and temporal information such as day time or night. When determined that the search
should be made, an optimal solution for the weighting coefficient is searched in regard
to a previously extracted traffic flow mode (ST002). The search method at this time
may involve a search for all values which can be taken by the weighting coefficient
(actually, all values which fall under a certain range), a branch limit method, a
mountain descending method, a neural net based search, an inheritance algorithm based
search, or the like. After the execution of the weighting coefficient optimal solution
search (including the case where the search is interrupted halfway without finding
an optimal solution), or when the search is not made, input information is inputted
from the input information storage unit (2 in Fig. 1) (ST003). After the input information
has been acquired, it is checked whether or not a cage allocation process has been
invoked (ST004). The processing flow returns to the processing at ST001 when the allocation
process is not invoked, and proceeds to the next processing when the allocation process
is invoked.
[0044] When the cage allocation process has been invoked, each elevator cage is preliminarily
allocated to a hall call (generally, a newly generated hall call) intended for the
allocation, and a cage loop process (ST005) is executed for calculating an evaluation
value for that case. This involves changing Ka from one to N in order (N designates
the number of group managed elevators), where Ka represents a preliminarily allocated
cage.
[0045] A forecasted trajectory is first calculated for the preliminary allocated cage of
the Ka-th car (ST006). This forecasted trajectory of the preliminary allocated cage
corresponds to the forecasted trajectory of the first car in Fig. 1(b). Next, a forecasted
trajectory is calculated for a cage K car (each car which satisfies K≠Ka) other than
the preliminarily allocated cage (ST007). This trajectory corresponds to the forecasted
trajectory of the second car in Fig. 1(b). Then, the interval evaluation time tref
is calculated (ST008) (an example of tref is shown in Fig. 1(b)), and a forecasted
interval value Bm (m=1, 2, ..., N) is calculated for each cage at the time point tref
(ST009). While a method of calculating the forecasted interval value will be described
later, the forecasted interval can be calculated from a temporal distance or a spatial
distance between respective positions based on the forecasted position of each cage
resulting from tref. Once the forecasted interval value has been calculated for each
cage, an interval evaluation value is calculated on the basis of the forecasted interval
values (ST010). This is represented by E(Ka) for the interval evaluation value when
a Ka-th car is preliminarily allocated. By repeating the preliminarily allocated cage
loop process, E(Ka=1), E(Ka=2), ... are calculated one by one.
[0046] As the interval evaluation value has been calculated, next calculated is a waiting
time evaluation value W(Ka) when the Ka-th car is preliminarily allocated (ST011).
A method of determining the waiting time evaluation value may involve using a waiting
time for a hall call, for setting the waiting time evaluation value, when the Ka-th
car is allocated to the hall call, or setting the waiting time evaluation value to
a maximum waiting time within hall calls served by the Ka-th car. Further alternative
methods may include a method of setting the waiting time evaluation value to an average
waiting time of hall calls served by all cars including the Ka-th car, a method of
setting the waiting time evaluation value to a square sum of waiting times associated
with hall calls served by all the cars including the Ka-th car, and the like.
[0047] After the interval evaluation value E(Ka) and waiting time evaluation value W(Ka)
have been calculated, the weighting coefficient WT is calculated (ST012). A weighting
coefficient calculation method has been generally described in connection with Fig.
2, and will be again described later in greater detail.
[0048] Next, a general evaluation value, which serves as an index for determining the allocation,
is calculated on the basis of the interval evaluation value, waiting time evaluation
value, and weighting coefficient (ST013). The general evaluation value is represented
by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0003)
where FT represents a function. More specifically, the general evaluation value is
represented by an equation of a linear sum, for example, like the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0004)
[0049] A sequence of processing from ST005 to ST013 described above is executed until the
preliminary cage allocation loop is completed (until the preliminarily allocation
process is executed for all the cages) (ST014). When not yet completed, a preliminarily
allocated cage is updated to the next car (ST015), and the process is executed from
ST006 for the updated preliminarily allocated cage of the Ka-th car. When the preliminary
cage allocation loop has been completed, the general evaluation values Φ(Ka=1), Φ(Ka=2),
..., Φ(Ka=N) are compared to determine an allocated elevator for the cage which has
the best evaluation value (ST016). After the determination of the allocation, the
flow returns to the first processing ST001 to repeatedly execute the process described
above.
[0050] Next, a weighting coefficient setting method according to the present invention will
be described with reference to Fig. 4.
[0051] Fig. 4 is a graph for describing a weighting coefficient setting method according
to one embodiment of the present invention, where the horizontal axis represents the
number of hall calls generated per round of an elevator, and the vertical axis represents
the weighting coefficient. Here, the number of hall calls generated per round of an
elevator represents an average of the number of hall calls which can be generated
while each of elevators managed in group makes a roud once (for example, from the
lowest floor in the upward direction to the lowest floor in the downward direction).
A larger number of hall calls are generated per round during a traffic jam, while
a smaller number of hall calls are generated in an inactive period.
[0052] While the graph of Fig. 4 has lines drawn to represent input/output characteristics
of three functions which includes a line F01 which represents a function for determining
an appropriate initial value WT
0 for the weighting coefficient; a line F02 which represents a function for determining
an appropriate upper limit value WT
upper limit for the weighting coefficient; and a line F03 which represents a function for
determining an appropriate lower limit value WTlower limit for the weighting coefficient.
The function (line F01) for determining an appropriate initial value for the weighting
coefficient is used by the weighting coefficient initial value calculation unit 12
in Fig. 2, while the function (line F02) for determining an appropriate upper limit
value for the weighting coefficient and the function (line F03) for determining an
appropriate lower limit value are used by the weighting coefficient range calculation
unit 11 in Fig. 2.
[0053] The three functions for determining the weighting coefficient have the following
four major features.
- 1) The ability to immediately find an initial value, an upper limit value, and a lower
limit value for an appropriate weighting coefficient from the number of generated
hall calls.
- 2) The ability to continuously determine the value for the weighting coefficient,
which is the output, in response to continuous variations in the number of hall calls
generated per round, which is an input variable.
- 3) The input variable is a scalar value (single variable).
- 4) The input variable can continuously take real numbers.
[0054] In other words, the value of the weight is calculated on the basis of functions which
continuously vary output values in response to variations in the input. Stated another
way, the value of the weight is calculated on the basis of functions which receive
real numbers and continuously vary the value. The advantages resulting from these
features will be described in connection with Fig. 8 in comparison with other setting
methods (Figs. 6 and 7).
[0055] As shown in the graph of Fig. 4, when the number of hall calls generated per round
is, for example, NA, the initial value WT
0 for the weighting coefficient is equal to F
0(NA), and the upper limit value WT
upper limit and lower limit value WT
lower limit are equal to F
upper limit (NA) and Flower limit (NA), respectively. Irrespective of how NA varies due
to variations in traffic demand, WT
0, WT
upper limit, and WT
lower limit can be immediately found. This constitutes a major characteristic. Also, each
function presents the value of zero on the vertical axis at all times for smaller
values on the horizontal axis from a value at which the value of zero on the vertical
axis intersects the horizontal axis.
[0056] While the graph of Fig. 4 shows an example in which the horizontal axis represents
the number of hall calls generated per round, similar effects can be provided as well
with a value based on the number of generated hall calls (for example, the number
of hall calls generated for a predetermined time, or the like), not limited to the
shown example. Further, similar effects can be provided as well using an index of
a scalar value related to traffic demand, not limited to the number of generated hall
calls. For example, similar effects can be provided as well with a value based on
the number of users, a value based on the total value of the number of generated hall
calls and the number of generated cage calls, an average waiting time, and the like.
[0057] The following description will be made on the reason for which an appropriate weighting
coefficient can be found by the functions as shown in Fig. 4 by entering the number
of hall calls generated per round of the elevator. The interval evaluation value (previously
described in connection with Fig. 2) is an index which evaluates a temporal interval
between cages, and this temporal interval between cages corresponds to a maximum waiting
time for a hall call possibly generated in the future. Therefore, the importance of
the interval evaluation value is strongly related to the number of hall calls possibly
generated in the future. For example, as a larger number of hall calls are generated
in the future, the interval should be made as temporally even as possible, so that
the interval evaluation value should be forced to more strongly act. Here, it is assumed
that the number of hall calls possibly generated in the future has a high correlation
with the number of hall calls generated per round at a particular time point or a
time point subsequent thereto. Therefore, a certain relationship is established between
the number of hall calls generated per round and an appropriate weighting efficient
value, and by representing this as functions as shown in Fig. 4, an appropriate weighting
coefficient (actually, an appropriate initial value and range) can be determined from
the number of hall calls generated per round of the elevator.
[0058] Fig. 5 is a conceptual diagram of an optimal solution search method for the weighting
coefficient according to one embodiment of the present invention. In Fig. 5, the horizontal
axis represents the value of the weighting coefficient, and the vertical axis represents
an average waiting time resulting from the execution of the group management control
simulation. For each value of the weighting coefficient WT on the horizontal axis,
a curve 901 represents the characteristic of the average waiting time when the group
management control of the present invention illustrated in Fig. 2 is simulated. In
the event of an optimal solution search for the weighting coefficient through repetitions
of the simulation, or in the event of a weighting coefficient optimal solution search
through the simulation shown in Fig. 2 (components designated by reference numerals
20, 21, 22 in Fig. 2), an arbitrary location on this characteristic curve 901 provides
an initial value (starting point). As such, a certain extent of time is required until
an optimal solution is reached. Particularly, for a traffic flow which appears for
the first time, the performance demonstrated in an initial stage (average waiting
time) can largely vary depending on where the initial value (starting point) is determined.
Also, in a transient period of the search, the search can be made in a wrong direction,
on the contrary, due to an insufficient number of times of the simulation. Accordingly,
in this embodiment, an appropriate initial value 902 for the weighting coefficient
can be immediately determined from the number of generated hall calls at a particular
time by using the continuous functions shown in Fig. 4, and an appropriate upper limit
value 903 and lower limit value 904 can also be immediately determined in a similar
manner. These actions are implemented by functional elements designated by reference
numerals 10, 11, 12, and 8 in Fig. 2. Further, after determining the appropriate initial
value and range, the optimal solution search is made within the range based on the
initial value, the optimal solution can be promptly and stably found.
[0059] In this connection, since the initial value WT
0, upper limit value WT
upper limit, and lower limit value WT
lower limit are determined in correspondence to the number of generated hall calls, these
values are variably adjusted in accordance with a traffic demand state at a particular
time point.
[0060] In the following, a description will be given of the superiority of the method of
setting the weighting coefficient using the function of the number of generated hall
calls as shown in Fig. 4, with a comparison with a method of setting the weighting
coefficient by entering a traffic flow and repeating a simulation. However, prior
to the description, a traffic flow will be outlined with reference to Fig. 6, and
an example of a weighting coefficient setting method will be described for the case
where the traffic flow is entered, with reference to Fig. 7.
[0061] Fig. 6 is a diagram showing an example of a weighting approach for a traffic flow
in a building having six floors. The leftmost table in Fig. 6 shows an OD (Origin-Destination)
matrix representative of a traffic flow. This OD matrix includes the origin represented
in a column direction (horizontal direction), and the destination in a row direction
(vertical direction), where each element in the matrix indicates the number of passengers
corresponding to elements of the row and column to which the element belong. For example,
the number of passengers who take the elevator on the second floor and get off the
elevator at the fifth floor is found to be three from the table. Also, the OD matrix
has six rows and six columns because the building has six floors. The traffic flow
refers to an integrated whole which represents the number of passengers on each floor,
and can be represented by such an OD matrix (the OD matrix is actually used for traffic
analysis intended for roads).
[0062] The second table (OD matrix) from the left in Fig. 6 represents the number of passengers
in each element in the form of variables tr1, tr2, ..., and presents a 30-adic vector
(tr1, tr2, tr3, ..., tr30). When one attempts to find the weighting coefficient using
such a traffic flow as it is, a 30-adic function must be found as shown in the following
equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0005)
[0063] This is a very complicated function, and it can be said that this function cannot
be actually analyzed. As such, instead of handling the 30-adic vector space as it
is, consider that it is divided into several main fragmental spaces. In doing so,
a finite number of fragmental spaces can be handled, which facilitates the handling.
These fragmental spaces correspond to traffic flow modes. In the following, this will
be described with reference to Fig. 7.
[0064] Fig. 7 is an explanatory diagram of an example of the weighting coefficient setting
method when a traffic flow is handled in an input. A building having two floors is
given herein as an example for simplifying the description. For a building having
two floor, an associated OD matrix is simply a 2x2 matrix as shown in Fig. 7(a), and
the traffic flow is represented by a two-dimensional vector (tr1, tr2). Here, the
traffic flow is represented by a two-dimensional graph as shown in Fig. 7(c), where
tr1 and tr2 are indicated on the horizontal axis and vertical axis, respectively.
A point on the graph of Fig. 7(c) represents a traffic flow. For example, a traffic
flow having large tr1 (large upward movements from the ground floor to the first floor)
and small tr2 (small upward movements from the first floor to the ground floor), such
as office-going time, is represented by the point as shown in the graph. Even for
a simple traffic flow in a building having two floors as shown in Fig. 7(c), a two-dimensional
plane of (tr1, tr2) is involved, and a complicated function must be handled if one
attempts to handle this with a function having two-dimensional variables as represented
by Equation (6):
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0006)
[0065] As such, representative traffic flows are collected into a single mass for the two-dimensional
plane of tr1, tr2 in Fig. 7(c). Fig. 7(d) shows an example, where the two-dimensional
plane of tr1, tr2 is divided into four areas. Then, representative traffic flow vectors
V1, V2, V3, V4 are defined for the four areas, respectively. V1, V2, V3, V4 denote
traffic flows representative of the whole, and correspond to the aforementioned traffic
flow modes. In this connection, the plane is not divided in a single way, but a variety
of divisions are contemplated in accordance with the characteristics of a particular
traffic demand in each building.
[0066] With the representation in traffic flow modes, a suitable weighting coefficient may
be defined for each traffic mode flow, as shown in Fig. 7(e). This optimal solution
can be found by repeatedly executing the simulation of the group management control
for the traffic flow modes while changing the weighting coefficients. For example,
in a scenario of Fig. 7(e), by repeatedly executing the simulation for a traffic flow
mode V3 while changing the weighting coefficients, an optimal weighting coefficient
for reducing an average waiting time can be determined to be WT=5.6. As an optimal
weighting coefficient is determined for each traffic flow mode through the simulation
in a similar manner, a resulting table shows the relationship between the traffic
flow modes and weighting coefficient, as shown in Fig. 7(f).
[0067] In summarizing the foregoing, when the traffic flow is handled in the input, a multi-dimensional
vector must be handled as it is, if any technique is not employed therefor, and complicated
processes are involved, so that the multi-dimensional vector is represented by principal
traffic flow modes, such that a weighting coefficient is set to each of the modes
by repeatedly executing the simulation.
[0068] Fig. 8 is a diagram showing a comparison of one embodiment of the present invention
with a conventional weighting coefficient setting method, where comparisons are made
according to several items for summarization. This table compares, for example, a
setting method disclosed in
JP-A-1-226676 with the setting method of this embodiment with respect to five items. In the following,
comparisons are made from the first item. First, for input variables, the prior art
uses a traffic flow vector or traffic flow modes which are main components extracted
from the traffic flow vector. In contrast, this embodiment uses the number of generated
hall calls. The nature of the respective input variables is a multi-dimensional vector,
for example, a vector such as tr1, tr2, tr3, ... in the prior art, but is a single
variable, in other words, a scalar value in this embodiment. Also, in regard to how
to determine a weighting coefficient which is an output value, the prior art selects
a weighting coefficient through a search by repeatedly executing a simulation of group
management control, whereas this embodiment sets a weighting coefficient using continuous
functions as shown in Fig. 4. Accordingly, the prior art is characterized by a certain
time required until the selection of a value, whereas this embodiment is characterized
by the ability to instantaneously determine a weighting coefficient.
This characteristic makes the method of this embodiment more advantageous over the
prior art in that an appropriate weighting coefficient (more precisely, an appropriate
initial value for the weighting coefficient) can be immediately set for a variety
of changes in traffic flow to stably exert the control performance.
[0069] Fig. 9 is a processing flow diagram which summarizes the weighting coefficient setting
method according to one embodiment of the present invention so far described. This
sequence of processing is executed in the hall call count calculation unit 10, weighting
coefficient range calculation unit 11, weighting coefficient initial value calculation
unit 12, traffic flow determination unit 20, weighting coefficient optimal solution
search unit 21, simulation unit 22, and weighting coefficient setting unit 8. The
sequence of processing will be described below in order. First, input information
is entered (ST101), and the number NA of hall calls generated per round is calculated
on the basis of the input information (ST102). This value can be calculated, for example
in the following manner. NA is calculated by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0007)
where NH represents the total number of hall calls generated for a predetermined time
which is set to a longer time than an average round time of the elevator at a particular
time point, and NR represents the total number of direction inversions.
[0070] The demoninator in Equation (7) corresponds to the total number of rounds of all
elevators for a predetermined time.
[0071] As the number NA of hall calls generated per round has been calculated, an initial
value WT
0 for the weighting coefficient is calculated by the function WT
0=F
0(NA) based on the number NA (ST103). Then, a traffic flow mode prevailing at that
time is determined (ST104), and it is determined whether or not a weighting coefficient
optimal solution search has been previously made for that traffic flow mode (ST105).
When the optimal solution search has been made to find the value of the weighting
coefficient which provides a better result than the initial value, the weighting coefficient
is set to this value (optimal solution at that time) (ST106). When the optimal solution
search has not been made, or when a value has not been found for the weighting coefficient
which provides a better result than the initial value, the value of the weighting
coefficient is set to the initial value WT
0 (ST107).
[0072] Since the weighting coefficient is set through the processing flow as illustrated
in Fig. 9, an appropriate weighting coefficient value can be immediately set based
on the initial value WT
0 determined by the function even for a traffic flow which appears for the first time
in a building of interest. Also, even in an initial stage of operation in a building,
an appropriate weighting coefficient value can be immediately set based on the initial
value WT
0 determined by the function. Further, an appropriate weighting coefficient value can
be immediately set based on the initial value WT
0 determined by the function even when the optimal solution search has not been converged
and an appropriate solution has not been found.
[0073] Fig. 10 is a processing flow diagram which summarizes the weighting coefficient optimal
solution search method according to one embodiment of the present invention. This
sequence of processing is performed by the hall call count calculation unit 10, weighting
coefficient range calculation unit 11, weighting coefficient initial value calculation
unit 12, traffic flow determination unit 20, weighting coefficient optimal solution
search unit 21, and simulation unit 22. The sequence of processing will be described
below in order. First, traffic flow mode data is entered (ST201), and it is determined
whether or not the optimal solution search process has been executed for the traffic
flow mode (ST202). When the process has been executed, an initial value for the search
is set to an optimal value found in the previous search (ST208). When the search process
has not been executed, the number NA of hall calls generated per round in that traffic
flow mode is calculated (ST203), and an initial value WT
0 for the weighting coefficient is calculated on the basis of the value NA (ST204),
an upper limit value WT
upper limit is calculated (ST205), and a lower limit value WT
lower limit is calculated (ST206). Then, the initial value for the search is set to WT
0.
[0074] The simulation of the group management control for the determined traffic flow mode
is executed for the set initial value, and the simulation is repeated while changing
the initial value to execute the optimal solution search (ST209). After the execution
of this optimal solution search (or halfway in the search), it is determined whether
or not the resulting optimal weighting coefficient falls within a range between the
upper limit value WT
upper limit and lower limit value WT
lower limit (ST210). When the optimal weighting coefficient falls within the range, this
weighting coefficient value provides the optimal solution. When not within the range,
the weighting coefficient value is set to the upper limit value WT
upper limit or the lower limit value WT
lower limit or an optimal solution found in the previous search (ST211).
[0075] Since the weighting coefficient optimal solution search is made through the processing
flow as illustrated in Fig. 10, the initial value for the search can be determined
to be an appropriate value using the function of the number of generated hall calls
even for a traffic flow which appears for the first time. As a result, the optimal
solution search can be made in a more efficient manner. Also, since the range of the
search is determined to be a proper range using the function of the number of generated
hall calls, the optimal solution search can be more efficiently made without searching
inappropriate regions even in an initial stage of the search or in a transient state.
It should be noted that these advantages have been described in Fig. 5 by showing
a search concept.
[0076] Fig. 11 illustrates in greater detail the input information storage unit 2 shown
in Fig. 2. The input information storage unit 2 stores the following data. First,
the data includes building facility data 201, group management elevator facility data
202, and current group management elevator state data 203.
Next, the data includes group management elevator state data statistics 204, state
data 205 on each hall in a building at a current time point, a building traffic flow
data 206, and temporal information data 207. The building facility data 201 stores
such data as the number of floors in a building, floor height of each floor, floors
intended for the service of the group management, and the like. The group management
elevator facility data 202 stores such data as the number of elevators managed in
group, a rated speed of each elevator car, a number limit of a cage, a door open/close
speed, a standard door open time, and the like. The current group management elevator
state data 203 includes such data as the positions of cages, information on the direction,
information on the speed, information on a load within a cage, allocated hall call
information, cage call information, information on stop floors, hall call continuation
time information on each hall call, a round time of each cage, and the like. The group
management elevator state data statistics 204 store such data as the number of hall
calls generated for a predetermined time , the number of generated cage calls, the
number of users, an average hall call continuation time, the number of times of direction
inversions, an average load, an average round time, and the like. The state data 205
on each hall in a building at a current time point stores such data as information
on hall call buttons 41A, 41B, information on cameras 51A, 51B of hall waiting customers,
and the like. The building traffic flow data 206 stores building traffic flow data
such as that shown by the OD matrix in Fig. 6. The temporal information data 207 stores
calendar information such as information by a clock, year, month, day, day of the
week, holidays, days on which special events take place, and the like. The input information
storage unit 2 stores all the data listed above. In this connection, the input information
storage unit 2 does not necessarily aggregate these data, but the data may be distributively
stored. In this event, the input information storage unit 2 may be regarded as a virtual
aggregate of these data.
[0077] The foregoing description has been so far made on the method of setting the weighting
coefficient. Next, a method of calculating a cage interval evaluation value will be
described in detail with reference to Fig. 12. The key to the method of calculating
the cage interval evaluation value is a method of setting a time for evaluating an
interval.
[0078] Fig. 12 illustrates in detail the configuration of the cage interval evaluation value
calculation unit 4 shown in Fig. 2. First, the cage interval evaluation value calculation
unit 4 comprises a forecasted trajectory calculation unit 401 for calculating a forecasted
trajectory of each cage in the future, and a forecasted cage interval calculation
unit 402 for calculating a cage interval after a predetermined time (interval evaluation
time tref, later described) based on the forecasted trajectory. Next, the cage interval
evaluation value calculation unit 4 comprises cage interval evaluation value calculation
unit 403 for calculating the cage interval evaluation value, and a furthest call search
unit 404 for finding the temporally furthest call (calls including hall calls and
cage calls) through a search. The cage interval evaluation value calculation unit
4 further comprises an interval evaluation time setting unit 405 for finding the interval
evaluation time tref based on a forecasted arrival time for the furthest call, i.e.,
a maximum forecasted arrival time.
[0079] In the following, the actions of the respective components in the interval evaluation
value calculation unit 4 of Fig. 12 sill be described with reference to Fig. 1 which
has been previously described. In Fig. 1(b), the forecasted trajectory calculation
unit 401 in Fig. 12 calculates forecasted trajectories (solid trajectories from a
current time point in the future direction in the diagram) of the first car and second
car. The interval evaluation time setting unit 405 sets the interval evaluation time
tref in Fig. 1(b). The forecasted cage interval calculation unit 402 in Fig. 12 finds
a forecasted position at the interval evaluation time from the forecasted trajectory
of each cage, i.e., the positions of the first car and second car drawn on the interval
evaluation time in Fig. 1(b), and finds a temporal interval or a spatial interval
of each cage from this forecasted position. The cage interval evaluation value calculation
unit 403 calculates an evaluation value for evaluating a cage interval uniformity
from the cage interval value. For example, when Fig. 1(b) is compared with Fig. 1(c),
Fig. 1(b) presents a higher cage interval uniformity, and the cage interval evaluation
value calculation unit 403 evaluates the uniformity.
[0080] One of important factors in calculating the cage interval evaluation value is a method
of setting a time at which the cage interval is estimated. This setting method also
constitutes a feature of this embodiment, so that the method of setting an interval
evaluation time will be described below with reference to Figs. 13 to 16.
[0081] Fig. 13 is a processing flow diagram for setting the interval evaluation time tref.
This sequence of processing is executed in the furthest call search unit 404 and interval
evaluation time setting unit 405 in Fig. 12. First, a cage loop process is executed
for searching each cage in order (ST501). Here, a cage intended for the search is
a K-th car (K=1, 2, ..., N). The initial value for K is one. First, all hall calls
allocated to the K-th car are searched to select a maximum forecasted arrival time
ART_H(K) (ST502). Next, all cage calls served by the K-th car are searched to select
a maximum forecasted arrival time ART_C(K) (ST503). Subsequently, ART_H(K) is compared
with ART_C(K) to employ the larger one for a forecasted arrival time ART_MAX(K) of
the furthest call associated with the K-th car (ST504). This forecasted arrival time
is represented by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0008)
[0082] It is determined whether or not the foregoing processing has been performed for all
elevator cars by checking whether or not K is equal to N (ST505). When not equal,
the value of K is incremented by one (ST506), followed by a return to the previous
processing (ST502). When the forecasted arrival times of the furthest calls have been
calculated for all the elevator cars, a maximum value of the forecasted arrival times
of the furthest calls associated with all the elevator cars is set to the interval
evaluation time tref (ST507). The interval evaluation time tref is represented by
the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0009)
[0083] In this way, a call which causes the maximum forecasted arrival time (the furthest
call for all cars) is selected for hall calls and cage calls served by all the elevators
at that time point, and the forecasted arrival time for the call is defined to be
the interval evaluation time. Advantages provided by determining the interval evaluation
time in this way will be described in connection with Fig. 14.
[0084] The value of the forecasted arrival time of the furthest call for all cars varies
from one allocation to another because new calls are generated over time (for example,
in course of approximately 20 seconds) to cause change in the value. As a result,
the interval evaluation time also varies in value each time the allocation is processed.
This shows that the situation of previously generated calls (situation of the number
of currently generated calls, and the like) varies from time to time, the interval
evaluation time is responsively adjusted as appropriate.
[0085] Fig. 14 shows the idea for the setting of the estimated interval time. The graph
of Fig. 14(a) represents a time axis on the horizontal axis on which a current time
is placed at the origin, and the floor position on the vertical axis. In the graph
of Fig. 14(a), two trajectories drawn in solid line represents forecasted trajectories
of the first car and second car, respectively. F10 represents the forecasted trajectory
of the first car, while F11 represents the forecasted trajectory of the second car.
The key to the interval evaluation time setting lies in at which time to evaluate
the interval between the two forecasted trajectories, where the interval evaluation
time has the nature as described below.
[0086] First, when the interval evaluation time is set in a region temporally close to the
current time, a problem is the inability to take into consideration the influence
of calls (hall calls or cage calls) previously accepted and to be served at later
times. This influence is particularly grave when passing occurs in the middle. For
example, assuming in the graph of Fig. 14(a) that the interval evaluation time is
set at a time indicated by reference numeral F12, it is determined that the subsequent
second car approaches to the preceding first car to result in a bunch state. Thus,
if an evaluation was made with the cage interval at this time (time F12), good control
would involve advancing the first car (allocation is restrained), and delaying the
second car (allocation is promoted). However, it can be seen from the forecasted trajectories
that the second car subsequently passes the first car, so that if the second car is
delayed, the bunch state will remain longer, on the contrary. In this way, when the
interval evaluation time is set in a region close to the current time point, a larger
influence is exerted due to a failure in taking into consideration those calls which
have been previously served by each elevator.
[0087] Next, assuming that the interval evaluation time is set in a region temporally far
away from the current time point, this scenario, which may come out in the future,
is highly susceptible to new hall calls and cage calls which can be generated at subsequent
times, so that the forecasted trajectories can largely change. For example, supposing
in Fig. 14(a) that the interval evaluation time is set at a time indicated by reference
numeral F13, new hall calls and cage calls are likely to be generated by this time,
possibly resulting in large uncertainty of the cage interval and large variations
in value in this scenario.
[0088] Fig. 14(b) is a graph showing the characteristic of the interval evaluation time
described above. In the graph of Fig. 14(b), the horizontal axis represents the interval
evaluation time, and the vertical axis represents a forecast accuracy when the cage
interval is estimated by a corresponding interval evaluation time. In a region where
the interval evaluation time is close to zero (corresponding to the current position),
the forecast accuracy for the cage interval is low, and the forecast accuracy increases
as the value of the interval evaluation time becomes larger from there. Then, the
forecast accuracy reaches a maximum at a certain value, and subsequently falls more
as the value becomes larger. The location at which the forecast accuracy reaches the
maximum is thought to be near the previously mentioned forecasted arrival time of
the furthest call for all the cars. This is because all hall calls and cage calls
which have previously been generated are included until the forecasted arrival time
for the furthest call so that all of them can be taken into consideration. Since there
is no call which has been previously generated at a time prior to this time, no reliable
information is available so that the forecast accuracy is simply lower.
[0089] Therefore, by setting the interval estimation time at or near the forecasted arrival
time of the furthest call for all cars, the cage interval evaluation can be made with
a high accuracy. As a result, the allocation can be carried out to more reliably approach
to an equidistance state, thus restraining a long waiting time.
[0090] Fig. 15 is a functional block diagram of a second embodiment of the cage interval
evaluation value calculation unit different from Fig. 12. In Fig. 15, components identical
to those shown in Fig. 12 are designated the same reference numerals, and a description
thereon is omitted. Fig. 15 differs from Fig. 12 in that the interval evaluation time
is set by a traffic flow mode which is prevailing at a particular time point. Specifically,
a traffic flow mode determination unit 406 determines a traffic flow mode which is
prevailing at a particular time point as a representative traffic flow vector of traffic
flow vectors which have previously prevailed in the building in the past. Then, an
interval evaluation time suitable for the traffic flow mode is referenced in an interval
evaluation time database 407 for the traffic flow mode to set a value therefor. Here,
the interval evaluation time database 407 for the traffic flow mode is a database
which arranges previously extracted traffic flow mode of the building and interval
evaluation times corresponding thereto in a tabular form. By using this, if the traffic
flow mode is determined, the interval evaluation time corresponding thereto can be
set by referencing the table.
[0091] Since the traffic flow is related to calls, an appropriate interval evaluation time
can be determined as well using the traffic flow mode instead of the forecasted arrival
time of the furthest call, and similar advantages can be expected.
[0092] In this connection, a time interval at which the interval evaluation time is set
is substantially equal to a time constant of a traffic flow change.
[0093] Fig. 16 is a functional block diagram of a third embodiment of the cage interval
evaluation value calculation unit different from Fig. 12. In Fig. 16, components shown
in Fig. 12 are designated the same reference numerals, and a description thereon is
omitted. Fig. 16 differs from Fig. 12 in that the interval evaluation time is determined
on the basis of an average round time at a particular time point. Specifically, an
average round time calculation unit 408 calculates an average round time T for all
elevators at a particular time point based on input information (entered from input
information storage unit 2 in Fig. 1). Based on the average round time T, an interval
evaluation time setting unit 405 determines the interval evaluation time tref according
to the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0010)
where F(T) represents a function of T. Equation (10) is represented, for example,
as follows:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0011)
where α represents a constant.
[0094] Similar to the traffic flow, the average round time is also related to calls, so
that an appropriate interval evaluation time can be determined as well using the average
round time instead of the forecasted arrival time of the furthest call, and similar
advantages can be expected.
[0095] As is the case with the aforementioned method of setting the interval evaluation
time, an important key for setting the interval evaluation value is a method of creating
a forecasted trajectory. The creation of the forecasted trajectory is performed in
a forecasted trajectory calculation unit 401 in Fig. 12, Fig. 15 or Fig. 16, or in
a forecasted route creation unit 411 in Fig. 17.
[0096] Fig. 17 is a functional block diagram of a fourth embodiment for the cage interval
evaluation value calculation unit 4 which substitutes for Fig. 12. While a representation
with a forecasted route is used herein, this forecasted route refers to the same as
the forecasted trajectory which has been so far described. Fig. 17 will be described
later in greater detail. In the following, the method of creating a forecasted trajectory,
which is a key of this embodiment, will be described with reference to Fig. 18.
[0097] Fig. 18 illustrates a general processing flow of a forecasted trajectory creation
method. In the following, the flow will be described. First, a variable K indicative
of a number of an elevator car is set to one (FA01). Next, it is determined whether
or not the K-th car is intended for the group management (FA08). Since elevator cars
which are separated from the group management for reasons such as a dedicated operation
are operated independently of the remaining elevators which are managed in group,
such elevators are removed from those intended for the creation of forecasted trajectory
through such processing. Next, it is determined whether or not the K-th car has a
direction (FA02). Here, the determination as to whether or not the K-th car has a
direction is, if in a different expression, equivalent to a determination made as
to whether or not the K-th car is servicing a hall call or a cage call. Accordingly,
when the K-th car is servicing a hall call or a cage call (when the K-th car has a
direction), the processing flow proceeds to a plural round forecasted arrival time
table creation process (FA03). When the K-th car is not servicing either a hall call
or a cage call (when the K-th car does not have a direction), the processing flow
proceeds to non-direction forecasted trajectory table creation process (FA05).
[0098] In the plural round forecasted arrival time table creation process (FA03), a forecasted
arrival time table is created for a plurality of rounds, for example, three or more
rounds. In the following, the forecasted arrival time tables for plural rounds are
represented by a variable tar_table(i, j, c, K), where i indicates a floor, j indicates
a direction, c indicates the number of rounds, and K indicates the name of a car.
The creation of the forecasted arrival time tables for plural rounds will be described
later in greater details in connection with Fig. 33. Once the forecasted arrival time
tables have been created for plural rounds, a forecasted trajectory table is created
for an elevator car having a direction, based on this table. The forecasted trajectory
table for an elevator car having a direction is represented by two variables ir(t,
K) and jr(t, K). Ir(t, K) represents a cage position of the K-th car t seconds after
a current time point, and jr(t, K) represents a cage direction of the K-th car t seconds
from the current time point. The creation of the forecasted trajectory table for the
elevator cage having a direction will be described later in greater detail in connection
with Figs. 25 and 26.
[0099] When the K-th car has no direction at the processing FA02, a forecasted trajectory
table is created for the car having no direction (FA05). Likewise, in this event,
the forecasted trajectory table is represented by the two variables ir(t, K) and jr(t,
K). The creation of the forecasted trajectory table for the elevator cage having no
direction will be described later in greater detail in connection with Fig. 27.
[0100] After the forecasted trajectory table has been created for the K-th car when it has
a direction or when it has no direction, K is incremented by one (FA06), and the processing
flow returns to processing FA08 to repeat the foregoing processing for a new K-th
car. This is executed for all cars intended for the group management (FA07).
[0101] There are two major features in the creation of the forecasted trajectory according
to this embodiment: 1) the forecasted arrival time table is created for a plurality
of rounds; and 2) the forecasted trajectory is created individually for a car which
has a direction and a car which has no direction. For example, in regard to 1), the
creation of a forecasted arrival time differs in accordance with the number of rounds
(described later in greater detail). In regard to 2), on the other hand, a trajectory
of a cage having a direction (trajectory FJ03 in Fig. 30) and a trajectory for a cage
having no direction (trajectory FJ02 in Fig. 30) are created in different shapes,
respectively, as shown in Fig. 30 (described later in greater detail). As a result,
highly accurate forecasted trajectories can be created in consideration of the state
of each car at a particular time point, and the state of traffic demand.
[0102] Fig. 19 is a processing flow diagram for creating the forecasted arrival time tables
for plural rounds according to one embodiment of the present invention. As previously
described, the forecasted arrival time table is represented by the variable tar_table(i,
j, c, K). Details are shown in Fig. 21, later described, which illustrates the creation
of exemplary forecasted arrival time tables for plural rounds, showing a forecasted
arrival time table FG02 for the first round, a forecasted arrival time table FG03
for the second round, and a forecasted arrival time table FG04 for the third round.
Such forecasted arrival time tables are created through the flow chart of Fig. 19.
[0103] First, initial values are set for a forecasted arrival time tar, variable i indicative
of the floor position of a K-th car, and a variable j indicative of the direction
of the K-th car (FB01). Specifically, tar is set to zero; i to a current cage position
of the K-th car; and j to a current cage direction of the K-th car. Next, a variable
c indictive of the number of rounds is set to one (FB02). This means that the forecasted
arrival time table is created from the first round. Next, a variable n indicative
of number of scans when each floor is scanned in order is reset to zero. This variable
n is incremented one by one (FB05), such that the process is repeated in loop until
n exceeds (n
max-1) (FB06). Here, n
max indicates total floor elements passed by the K-th car, and is represented by the
following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0012)
[0104] The meaning represented by the value of 2(n
max-1) will be described in connection with the leftmost table FG01 in Fig. 22. The leftmost
table in Fig. 22 indicates the floor in the row direction, and the upward direction
and downward direction in the column direction, where a display method is such an
elevator is represented by a ring which makes a round. In this table, there are six
floors, but the upward direction on the fifth floor, which is the highest floor, and
the downward direction on the ground floor, which is the lowest floor, are omitted
because they are substantially meaningless. As a result, the number of effective floors
is calculated to be 34 (6x6-2=34). This matches the value derived from 2(n
max-1) when n
max=6. Stated another way, n indicates a floor to be scanned when the floors are scanned
on a floor-by-floor basis on the assumption that one round of the elevator complies
with the leftmost table of Fig. 22, where 2(n
max- 1) indicates the number of all floors which are scanned per round.
[0105] Forecasted arrival time tables tar_table (i, j, c, K) for plural rounds are calculated
for each n (FB04). This is executed in a forecasted arrival time table calculation
routine, later described (described later in connection with Fig. 20). As described
above, this process is executed 2(n
max- 1) times (FB06), followed by the calculation for the next round, so that the variable
c indicative of the number of rounds is incremented by one. In this way, a forecasted
arrival time table tar_table (i, j, c=1, K) for c=1 (first round), and a forecasted
arrival time table tar-Table (i, j, c=2, K) for c=2 (second round) are calculated.
Further, a forecasted arrival time table tar_table (i, j, c=3, K) for c=3 (third round)
is c alculated, and the process is repeated until a forecasted arrival time on the
final arrival floor in each round exceeds t
max (FB08).
[0106] In the sequence of processing described above, the forecasted arrival time tables
for plural rounds can be created, as shown in Fig. 22. In the following, the forecasted
arrival time table calculation routine (FB04 in Fig. 19) will be described in greater
detail with reference to Fig. 20.
[0107] Fig. 20 illustrates a processing flow diagram of the forecasted arrival time table
calculation routine (FB04 in Fig. 19). First, a rough flow of processing will be verbally
described. 1) A variable tar is established for a forecasted arrival time. 2) The
next move floor is set (the floor number is decremented by one when in the upward
direction, and incremented by one when in the downward direction). 3) it is determined
whether or not the number of rounds is the first round or second round. 4) When in
the first round, a stop time is added to tar when a call stop is present on a floor
of interest, and a stop probability is added to tar when no call stop is present.
5) Wen in the second round onward, the stop probability is added to tar. 6) A time
required for a movement to the next floor is added to tar. 7) the value tar_table
(i, j, c, K) of the forecasted arrival time table of the floor of interest is set
in tar.
[0108] Fig. 20, in which a rough flow of processing is as described above, will be described
in greater detail. Here, a floor to be scanned for a K-th car is indicated by i, and
the direction is indicated by j. First, in a process of each scan of the K-th car
of interest (floors are scanned in a ring shape), it is determined whether or not
the cage direction j is the upward direction (FC01). When in the upward direction,
a floor resulting from a subtraction of one from the variable i indicative of the
cage position during a scan is a next move floor i2 (FC02). When in the downward direction,
a floor resulting from an addition of one to i is i2 (FC03). It is determined whether
or not the next move floor i2 is a direction inversion floor of the K-th car (for
example, the highest floor or lowest floor) (FC04). When i2 is a direction inversion
floor, the direction j2 on the next move floor is set to the direction opposite to
j (FC05). The setting of the direction inversion floor on a car-by-car basis in this
way is one key of the present invention. When i2 is not a direction inversion floor,
i2 is set to the same direction as j (FC14).
[0109] It is determined whether or not the floor/direction (i, j) which are being scanned
are a floor serviced by the K-th car (FC06). When the floor/direction (i, j) are not
a floor not serviced by the K-th car, no call stop will occur, the processing flow
skips processing associated with the following stop, and goes to processing FC11.
[0110] When the floor/direction (i, j) are a floor serviced by the K-th car, it is next
determined whether or not the number of rounds c of the forecasted arrival time table
creation is two or more (FC07). When c is the second round or later, an expected stop
time value calculated from a stop probability is used for all floors serviced by the
K-th car, on the assumption that no call stop will occur in that round (FC10). This
corresponds to a forecasted stop time which is forecasted by probability. This is
a key of this embodiment. Specifically, the expected stop time value for the (i, j)
floor/direction is added to the variable tar indicative of the forecasted arrival
time.
[0111] When c is the first round, it is determined whether or not a stop is caused by a
hall call or a cage call for the floor/direction (i, j) which are being scanned (FC08).
When there is a call stop, a stop time at that floor is added to tar (FC09). When
there is no call stop, an expected stop time value of (i, j) floor/direction is added
to tar (FC10). One key of the present invention lies in that the expected stop time
value is considered for the first round as well for a serviced floor without call
stop. In this connection, the stop time of each floor/direction and expected stop
time value are updated at all times corresponding to a change in the traffic flow
(FC15). For example, during an office-going rush hours, the expected stop time value
of each floor/upward direction is increased, while during semi-rush hours before lunch
time, the expected stop time value of each floor/downward direction is increased.
[0112] Upon completion of the foregoing processing associated with reflection of the call
stop, a move time tmv (i2, j2), which is taken when a movement is made from (i,j)
floor/direction to (i2, j2) floor/direction, is added to tar (FC11). In this way,
the stop time and move time are added to calculate a forecasted arrival time to (i2,
j2) floor/direction of the destination. I is updated to i2, and j to j2 (FC12), and
the value tar_table (i, j, c, K) of the forecasted arrival time table for a new (i,
j) floor/direction is set to tar (FC13). The foregoing process is the process of the
forecasted arrival time table calculation table, and is recursively executed while
changing i, j, c, K in the loop process of Fig. 19 to complete the forecasted arrival
time tables tar_table (i, j, c, K).
[0113] The features of the forecasted arrival time tables for plural rounds described above
may be summarized in the following manner. 1) A direction inversion floor is set for
each car. 2) For the forecasted arrival time table for the first round, a stop time
associated with a currently generated call (hall call, cage call) is used together
with the expected stop time value for a call which has not been generated. 3) In the
second round onward, the expected stop time value is used on the assumption that no
call has been generated. 4) The stop time and expected stop time values have set values
for each combination of floor/direction. 5) The stop time and expected stop time value
vary (are updated) corresponding to a traffic flow. Since forecasted trajectories
are created in one embodiment of the present invention based on the forecasted arrival
time tables for plural rounds, which have the features as listed above, elaborate
forecasted trajectories can be created with a high forecast accuracy in accordance
with the characteristics of each ar, state of call stop, and traffic flow state. As
a result, it is possible to accurately evaluate the cage interval and the like based
on the forecasted trajectories and reduce a waiting time.
[0114] In the following, specific examples of the forecasted arrival time tables for plural
rounds will be described with reference to Figs. 21 and 22. First, Fig. 21 shows (a)
a stop time table, (b) a stop probability table, and (c) an expected stop time value
table in each of floors and directions, respectively. First, the stop time table of
Fig. 21(a) indicates stop times for each of the floors and directions. In this example,
the same stop time (eight seconds) is set on all the floors in both directions, but
different stop times may be defined on a floor-by-floor and/or direction-by-direction
basis.
[0115] The stop probability table of Fig. 21(b) indicates the stop probability for each
of the floors and directions. For example, the stop probability on the third floor
in the upward direction is set to 0.6, which means that the elevator can be stopped
by a call with a probability of 0.6 while it makes a round. In the example of Fig.
21(b), the stop probability is different between the upward and downward directions
in order to reflect the fact that the traffic demand at that time point tends to stop
in the upward direction. In this way, the stop probability reflects the traffic demand
(or traffic flow) at a particular time point, so that the value of each floor/direction
of the stop probability varies in response to a change in the traffic demand.
[0116] The expected stop time value table of Fig. 21(c) indicates the expected stop time
value for each of the floors and directions. This expected stop time value is calculated
by multiplying the stop time by the stop probability. In this embodiment, this value
is used as a forecasted stop time (expected value for the stop time) for a floor on
which no hall call or a cage call has been generated.
[0117] Fig. 22 shows a specific example of the forecasted arrival time tables for plural
rounds which are calculated using the stop time table, stop probability table, and
expected stop time table shown in Fig. 21. First, the leftmost table (FG01) of Fig.
22 represents a situation of the first car at a current time. The first car (FG05)
is positioned on the first floor toward the upward direction (FG05), and is going
to serve a hall call in the upward direction on the second floor (FG06) a cage call
on the fourth floor (FG07), and a hall call in the downward direction on the fourth
floor (FG08). Accordingly, the first car stops on the second floor in the upward direction,
the fourth floor in the upward direction, and the fourth floor in the downward direction,
respectively.
[0118] The forecasted arrival time tables for the first round, second round, and third round
of the first car are indicated by reference numerals FG02, FG03, FG04, respectively,
in Fig. 22. First, in the forecasted arrival time table (FG02) for the first round,
since the first car is currently positioned on the first floor in the upward direction,
the table begins with the second floor in the upward direction and makes a round to
end with the first floor in the upward direction (FG10). The forecasted arrival time
on the second floor in the upward direction is two seconds because only a movement
is involved, whereas the forecasted arrival time on the third floor in the upward
direction is 12 seconds which is calculated by adding ten seconds (8+2=10) because
the first car must stop on the second floor. The forecasted arrival time on the fourth
floor in the upward direction is calculated to be 18.8 seconds by adding the expected
stop time value and a time required for a movement (4.8+2=6.8) to 12 seconds. The
forecasted arrival time on the fifth floor in the downward direction is calculated
to be 28.8 seconds by adding ten seconds (8+2=10) because the first car must stop
on the fourth floor in the upward direction. The forecasted arrival time on the fourth
floor in the downward direction is calculated to be 32.4 seconds by adding the expected
stop time value and the time required for the movement (1.6+2=3.6 seconds) to 28.8
seconds. Subsequently, similar calculations are repeated to complete the forecasted
arrival time table for the first round.
This sequence of processing is the same as the flow chart of Fig. 20. The forecasted
arrival time table (FG03) for the second round, as the table for the first round,
begins with the second floor in the upward direction (FG11), and make a round to end
with the first floor in the upward direction (FG12). In this second round, the forecasted
arrival times are all calculated using the expected stop time values associated therewith.
For example, the forecasted arrival time on the third floor in the upward direction
in the second round is calculated to be 73.6 seconds by adding 6.8 seconds (4.8+2=6.8)
to the forecasted arrival time 66.8 seconds on the second floor in the upward direction.
In a similar manner, the forecasted arrival time table (FG04) for the third round
is calculated as shown.
[0119] Next, the creation of the forecasted trajectory table for an elevator car having
a direction (process FA04 in Fig. 18), described in connection with Fig. 18, will
be described in detail. While this creation process is illustrated by processing flows
in Figs. 25 and 26, later described, a general flow of the process will be first described
roughly with reference to Figs. 23 and 24
[0120] First, Fig. 23 shows an example of a finally created forecasted trajectory table.
As shown, the forecasted trajectory table stores, for each car (a column designated
FH02 for the first car, and a column designated FH03 for the second car), data on
a forecasted position (FH04 for the first car) of each car at each time (column FH01),
and the direction (FH05 for the first car). By tracing the data on the time axis,
a forecasted trajectory can be created for each car.
[0121] The forecasted trajectory table of Fig. 23 is created from the data in the forecasted
arrival time tables for plural rounds in Fig. 22. Specifically, a forecasted position
at each time can be calculated through interpolation from forecasted arrival times
of adjacent ones of respective floors and directions. This calculation method is conceptually
shown in Fig. 24.
[0122] In Fig. 24, the right-hand figure shows a graph which indicates the time on the horizontal
axis, and floor positions on the vertical axis. A line FF01 on this graph is drawn
by connecting points (tx, ix) representative of each floor/direction of a K-th car
and its forecasted arrival time on a two-dimensional coordinates, with line segments.
This line FF01 is the original shape of the forecasted trajectory. The left-hand figure
indicates the position and direction (FF02) of the K-th car at a current time, from
which it can be seen that the K-th car is positioned on the first floor in the upward
direction. Accordingly, the line FF01 in the right-hand figure has a point FF02 plotted
at first floor/upward direction at time zero (current time).
[0123] On the line FF01, a point FF03 represents the position and forecasted arrival time
of the K-th car on the second floor in the upward direction, and a point FF03 represents
the position and forecasted arrival time of the K-th car on the adjacent third floor
in the upward direction. Assuming that the coordinates of the point FF03 are preliminarily
designated by (tA, iA), and the coordinates of the point FF04 by (tB, iB), an arbitrary
point (t, ir(t, K)) on a line segment which connects these two points can be represented
by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0013)
[0124] Stated another way, under a condition tA≦t≦tB, a forecasted position ir(t, K) of
a cage at a time t can be calculated once t is determined. Also, a forecasted cage
direction jr(t, K) can also be calculated from the slope of that section. Here, two
points are defined on the second floor in the upward direction and the third floor
in the upward direction. As this is shifted one by one, a forecasted position ir(t,
K) and direction jr(t, K) of a corresponding cage can be calculated for all times
t. This idea is relied on to create the forecasted trajectory table of Fig. 23 from
the data in the forecasted arrival time tables for plural rounds as shown in Fig.
22. In summary, a forecasted position ir(t, K) at a time t between two corresponding
times is calculated in accordance with Equation (13) from data on the direction and
forecasted arrival time of two adjacent floor/direction in the forecasted arrival
time tables for plural rounds as shown in Fig. 22. The floor/direction is shifted
one by one to find t, ir(t, K), jr(t, K) over regions of plural rounds. This results
in the forecasted trajectory table as shown in Fig. 23.
[0125] A rough concept of the creation of the forecasted trajectory table has been described
above. In the following a specific processing flow will be described with reference
to Figs. 25 and 26. Figs. 25 and 26 illustrate the flow of the creation of a forecasted
trajectory table divided into two pieces.
[0126] Referring first to Fig. 25, initial values are first set (FD01). Here, a time variable
parameter t of the forecasted trajectory table is set to zero, and a variable parameter
c indicative of the number of rounds to zero. Also, a flag variable z indicative of
whether or not calculations have been completed for initial floors (which require
special processing for adding a time origin) is set to zero, and a variable parameter
i indicative of the position of a scanned floor is set to a cage position of a K-th
car at a current time, and a variable parameter j indicative of the direction of a
scanned floor is set to a direction at the current time point. Next, a variable n
indicative of the number of a scanned floor is set to zero. The meaning of this n
is the same as the n used in Fig. 19, where when the value of n reaches 2(n
max-1), floors in one round have just been scanned. This addition of n is performed in
processing FD24 in Fig. 26, and a determination as to one round has been reached (whether
or not n=2(n
max-1) is established) is made in processing FD13, FD25. Nest, it is determined whether
or not the flag variable z is zero (FD03). When the flag variable z is zero, the first
floor is being processed, in which case alone different processing is performed.
[0127] When the flag variable z is zero, the variable iA is set to i (currently scanned
floor), the variable jA is set to j (the direction of the currently scanned floor)
(FD04), and tA is set to zero (FD05). When the flag variable z is not zero, the variable
iA is set to i, and the variable jA to j (FD06), and tA is set as shown in the following
equation based on the forecasted arrival time tables for plural rounds (FD07).
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0014)
[0128] In other words, tA is set to a forecasted arrival time on a floor (iA, jA) for the
K-th car in a c-th round. The variables iA, tA correspond to iA, tA shown in Fig.
24, respectively (corresponding to the point FF03 in Fig. 23). It should be noted
that jA represents a direction for iA. In other words, from two points (tA, iA) and
(tB, iB), a time t between them, and a forecasted arrival time ir (t, K) are calculated,
where a starting point of the two points is defined.
[0129] Next, it is determined whether or not the direction j of the currently scanned floor
is the upward direction (FD08). The variable iB is decremented by one when in the
upward direction (FD9), and incremeneted by one when in the downward direction (FD10).
Here, the variable iB corresponds to iB shown in Fig. 24 (point FF04 in Fig. 24).
This indicates the position of the end point out of the two points. It is determined
whether or not iB is a direction inversion floor for the K-th car (FD11). The variable
jB is set to the direction opposite to j when iB is a direction inversion floor (FD12),
and otherwise set to the same direction as j (FD27). Further, it is determined whether
or not the variable n indicative of the number of scanned floor reaches 2(n
max-1) (FD13). As has been previously described, this determination is made to see whether
or not all floors included in one round have been scanned. When the number of scanned
floors is less than the number of floors in one round, tB is set to tar_table(iB,
jB, c, K) (FD14). When the number of scanned floors is equal to the number of floors
in one round, tB is set to tar_table(iB, jB, c+1, K) (FD15). The latter case means
that since floors in one round have been scanned, a value is reference for tB from
a forecasted arrival time table tar_table (iB, jB, c+1, K) by adding one to c. The
following processing continues on (b) in Fig. 26.
[0130] The process following (b) in Fig. 26 will be described below. Since (tA, iA) and
(tB, iB) have been respectively set, the value of ir(t, K) is calculated by equation
(13) (FD16). This is the same as the calculation of the value of the point (t, ir(t,
K)) on the line segment (tA, iA) - (tB, iB) by equation (13) in Fig. 24. Next, the
direction jr(t, K) is determined to be in the same direction as jA (FD17).
[0131] Once ir(t, K) and jr(t, K) have been calculated for t, Δt is added to t to update
t (FD18), and ir(t, K) and jr(t, K) are calculated for the new t). Here, when t exceeds
t
max, the process for creating the forecasted trajectory table is terminated (FD19). t
max corresponds to a time width of the forecasted trajectory, and has been previously
set to a predetermined value. A specific value for t
max is preferably larger than the interval evaluation time tref described in connection
with Fig. 12, and is therefore preferably longer than the forecasted arrival time
of the furthest call. When the control is conducted in accordance with a forecasted
trajectory of a long term, to some degree, t
max is preferably equal to or longer than a time required for one round of the elevator
(for example, 60 seconds or longer).
[0132] When t is equal to or larger than tB (FD20), i is set to iB, and j is set to jB (FD22).
This corresponds to a procedure, when considering in Fig. 24, in which t is started
from tA and advanced by adding Δt, and when t exceeds tB, the process goes to the
next section. Also, in this event, it is determined whether or not the flag variable
z is zero (FD22), and z is set to one when flag variable z is zero (FD23). This processing
means that a section in which the time zero is started has been left out, so that
this is indicated by the flag variable z. A change to a section means a transition
of a scanned floor to the next floor on the forecasted arrival time table, and n is
incremented by one (FD24). Further, it is determined whether or not n exceeds 2(n
max-1), and the variable c indicative of the number of rounds is incremented by one when
n exceeds 2(n
max-1). This means a transition to the forecasted arrival time table for the next round.
[0133] Finally, turning back to Fig. 18, the process for creating the forecasted trajectory
when an elevator car has no direction (serves neither a hall call nor a cage call),
shown at FA05 in Fig. 18, will be described in greater detail. A flow diagram of the
process for creating the forecasted trajectory when an elevator car has no direction
is illustrated in Fig. 27.
[0134] The process in Fig. 27 will be described below. First, in initial settings, the variable
parameter t indicative of the time is set to zero (FE01). Next, the variable ir(t,
K) indicative of the cage position of the K-th car in the time t is set to the cage
position at a current time, and the variable jr(t, k) indicative of the cage direction
is set to non-direction (FE02). Δt is added to the value of t (FE03), and the processing
FE02, FE03 is repeated until t exceeds t
max (FE04). Such a process is performed on the assumption that a non-direction elevator
remains stand-by at the current position.
[0135] Through the sequence of the processes illustrated in Figs. 18 - 20 and Figs. 25 -
27, data can be created for the forecasted arrival time tables for plural rounds (one
example of which is shown in Fig. 22), and data can also be created for the forecasted
trajectory table (one example of which is shown in Fig. 23). Data for the forecasted
trajectory table shows the position and direction of each elevator car from the current
time point to each time advance, as shown in Fig. 23, and this corresponds to the
forecasted trajectory. The creation method shown in this embodiment is a distinctive
creation method which more copes with an actual situation in order to increase the
forecast accuracy, and for this reason, the forecasted trajectory also exhibits a
distinctive shape. In the following, the features of the forecasted trajectory which
can be created by this embodiment will be described with reference to Figs. 28 to
35.
[0136] Fig. 28 shows diagrams of an example of the forecasted trajectories which are created
by the forecasted trajectory creation method shown in this embodiment. Here, a right-hand
diagram FI01 shows forecasted trajectories of the first car and second car, respectively.
The forecasted trajectory of the first car is represented by a solid line FI02, and
the forecasted trajectory of the second car is represented by a broken line FI03.
Also, the state of the first car at a current time point, i.e., the cage position/direction,
and a hall call and cage call served situation are shown in the leftmost table designated
by reference numeral FI04, and the state of the second car at the current time point
is shown in the left-hand table designated by reference numeral FI05.
[0137] Referring first to the forecasted trajectory FI02 of the first car, stops caused
by a hall call and a cage call are represented by changes in sloping angle in the
first round, i.e., from the first floor in the upward direction to the ground floor
in the upward direction. However, in the second round onward, the forecasted trajectory
is represented by straight lines FI106, FI107 and is represented only by the expected
stop time value based on the stop probability. As a result, as shown, in contrast
to the trajectory in the first round, the trajectory in the second round onward has
the same shape in each round. Also, since the stop probability is reflected, the upward
slope (FI06) is different from the downward slope (FI07) for the trajectory in the
second round onward. The slop of the trajectory reflects the stop probability, and
the stop probability is set in correspondence to a change in the traffic flow, where
the slope varies in accordance with the traffic flow. If the stop probability is not
reflected, the slope of the forecasted trajectory is determined only by the speed
of the elevator, resulting in the same or symmetric slopes of the trajectory in the
upward direction and downward direction. It should be noted that data on the stop
time, stop probability, and expected stop time value used in the forecasted trajectories
of Fig. 28 are those shown in Fig. 21.
[0138] Also, the respective forecasted trajectories present trajectories which invert in
direction on the highest floor and lowest floor. One reason for creating such trajectories
which invert in direction on the extreme floors (highest floor or lowest floor) is
that the evaluation based on the forecasted trajectory of each car aims at a temporally
equidistant state, which is particularly effective during rush hours. It is anticipated
that a large number of hall calls and cage calls are generated during rush hours,
and as a result, actual operation trajectories also invert to the opposite direction
on the extreme floors, as shown in Fig. 28. Accordingly, the forecasted trajectories
are also created to invert in direction on the extreme floors.
[0139] Fig. 29 is an explanatory diagram for forecasted trajectories which place importance
on inactive hours, where the elevator cars can remain stand-by. During inactive hours,
the forecasted trajectories need not invert on the extreme floors at all time as shown
in Fig. 28, but may be created such that elevator cars remains stand-by at a forecasted
floor at which a call service is over after a forecasted time at which the call service
is over, as shown in Fig. 29. Specifically, a forecasted trajectory creating means
creates a forecasted trajectory of an elevator which does not have a hall call or
a cage call allocated thereto to be parallel with the time axis. In this event, the
forecasted trajectory creating means estimates a final cage call floor from a traffic
demand at a particular time, and creates a forecasted trajectory which forces the
elevator to subsequently wait at that floor. For example, in the case of Fig. 29,
it is forecasted that the first car (forecasted trajectory FQ01) will be on the first
floor in the downward direction after serving the last cage call, and the resulting
forecasted trajectory [FQ02] shows that the first car subsequently remains stand-by
on the first floor in the downward direction. Likewise, it is forecasted that the
second car (forecasted trajectory FQ03) will be on the fourth floor in the upward
direction after serving the last cage call, and the resulting forecasted trajectory
[FQ04] shows that the second car subsequently remains stand-by on the fourth floor
in the upward direction.
[0140] Turning back to Fig. 28, reviewing the forecasted trajectory FI02 of the first car
and the forecasted trajectory FI03 of the second car in Fig. 28, they are substantially
equidistantly spaced in terms of the position at the current time point, but it is
anticipated that they will come close to each other from then on depending on a subsequent
serving situation and an expected stop time value situation.
By thus drawing the forecasted trajectories, it is possible to forecast beforehand
a situation which can occur at a future time by creating the forecasted trajectory
of each car, and by reflecting this information to the hall call allocation, the actual
trajectories can be properly controlled. For example, by evaluating the interval between
the forecasted trajectory FI02 of the first car and the forecasted trajectory FI03
of the second car (a quantitative evaluation can be made with an area sandwiched by
the trajectories) before and after the assignment of each car, it is possible to evaluate
the degree of deviation between two cars in the future. Also, by reviewing the tendency
(temporal change) of the interval between the forecasted trajectories of the two cars,
it is possible to evaluate a temporal change in the interval between the trajectories
(for example, approaching to a bunch operation state or the like).
[0141] As described above, the forecasted trajectories according to this embodiment can
be created with a high forecast accuracy because a stop caused by a currently generated
call and a probabilistic stop possibly caused by a call not generated are taken into
consideration, and are reflected to the trajectories by a method which follows the
actuality.
[0142] Fig. 30 shows a second example of forecasted trajectories by the creation method
shown in this embodiment. A forecasted trajectory of the first car is represented
by a solid line FJ02, and a forecasted trajectory of the second car is represented
by a broken line FJ03. Also, a situation of the first cage at a current time point,
i.e., the cage position/direction and a hall call and cage call serving situation
are shown in a table designated by reference numeral FJ04, and a situation of the
second cage is shown in a table designated by reference numeral FJ05.
[0143] As can be understood from reference numeral FJ04 in Fig. 30, the first car remains
stand-by on the third floor without having a call service. Therefore, the forecasted
trajectory FJ02 of the first car shows that the first car remains stand-by on the
third floor. This trajectory of the car having no direction is first sent to the forecasted
trajectory table creation process (FA05 in Fig. 18) for an elevator car having no
direction by the general processing flow of the forecasted trajectory creation illustrated
in Fig. 18, and detailed data are crated by the processing flow for a car having no
direction, illustrated in Fig. 27.
[0144] Fig. 31 shows a third example of forecasted trajectories according to the creation
method shown in this embodiment. In this example, examples of forecasted trajectories
are shown when the stop probability differs among respective floors/directions. The
left-hand diagram (FK04) in Fig. 31 shows the cage position and direction at a current
time, where the first car (FK05) and second car (FK06) are at the positions toward
the directions shown in the diagram, respectively. It should be noted that in this
diagram (FK04), calls served by each car are omitted.
[0145] The right-hand diagram (FK01) in Fig. 31 shows forecasted trajectories of the two
elevator cars. The forecasted trajectory of the first car is represented by a solid
line FK02, and the forecasted trajectory of the second car is represented by a broken
line FK03. The forecasted trajectories in Fig. 31 differ from the forecasted trajectories
in Fig. 28 in that the slopes of the forecasted trajectories are different for each
floor/direction because of a difference in the stop probability among the respective
floors/directions in the forecasted trajectories of Fig. 31. Generally, the stop probability
differs because the trend of users differs among respective floors/directions. Accordingly,
it an be said that the shape of the forecasted trajectories in Fig. 31, which reflect
respective stop probabilities to the respective floors/directions provides the highest
accuracy. Further, since the stop probability for each floor/direction varies following
variations in the traffic flow, forecasted trajectories are created in a variety of
shapes, reflecting the variations in the traffic flow.
[0146] Further, in the forecasted trajectories based on the individual stop probabilities
determined for the respective floors and directions, since the shape of the forecasted
trajectory is precisely defined for each floor/direction, the evaluation can be made
with a higher accuracy than when the interval between forecasted trajectories of respective
cars is evaluated. Accordingly, by using the forecasted trajectories based on the
individual stop probabilities determined for the respective floors and directions,
it is possible to increase the accuracy of interval evaluation, provide more proper
allocation in controlling the interval, and reduce a long waiting time.
[0147] Fig. 32 shows a fourth example of the forecasted trajectory according to the creation
method shown in this embodiment. The forecasted trajectory in Fig. 32 differ from
the forecasted trajectories in Fig. 28 in that they are in such shapes that explicitly
reveal elements of stops caused by calls on the forecasted trajectories and probabilistic
stops determined by the stop probability. In the forecasted trajectory FL02 in Fig.
32, a portion of a call stop is indicated by an element (FL03) on a horizontal section
of the trajectory on the fourth floor in the downward direction in the first round,
and a portion of a probabilistic stop is indicated by an element (FL04) on a horizontal
section of the trajectory on the third floor in the upward direction in the first
round. An element (FL05) represented by an oblique line segment indicates a downward
movement state.
[0148] One advantage of the forecasted trajectory shown in Fig. 32 is that a highly accurate
forecasted trajectory which reflects an actual shape can be created by dividing three
elements, stop caused by a call, probabilistic stop, and movement in detail. Actual
movements of an elevator does not match the trajectory represented by an oblique line
on the time axis as shown in Fig. 28, but involves horizontal sections because the
elevator must stop. As such, the forecasted trajectory in Fig. 32 more reflects the
actual state. Also, another advantage of the forecasted trajectory in Fig. 32 is the
ability to visually readily classify the three elements, i.e., call stop, probabilistic
stop, and movement. With such a shape, it is possible to understand where a call stop
is present, how the situation of the stop probability is for each floor/direction,
and how the call stop and stop probability affect the trend of the trajectory at first
sight. For example, when the forecasted trajectories of the first car and second car
shows that the first car and second car will fall into a bunch operation in the future,
it can be understood whether this is caused by impartial stop probabilities in the
floor/direction or allocation of call stops.
[0149] For the forecasted trajectory as shown in Fig. 32, the creation of data of the forecasted
trajectory data may be divided into stop, probabilistic stop, and movement. For example,
in course of creating the forecasted arrival time table for plural rounds, a process
of adding a call stop time or an expected stop time value, and adding a move time,
where they may be separately stored in data.
[0150] Fig. 33 shows a fifth example of the forecasted trajectories according to the forecasted
trajectory creation method shown in this embodiment. The forecasted trajectories shown
in Fig. 33 differ from the forecasted trajectories shown in Fig. 28 in that the forecasted
trajectories in Fig. 33 are represented by rough trajectories according to the direction,
i.e., in the upward and downward directions. Specifically, the forecasted trajectories
in Fig. 33 can be created by connecting points on the highest floor with points on
the lowest floor of the forecasted trajectories in Fig. 28. They correspond to forecasted
trajectories which are based on data resulting from accumulating times of call stop,
probabilistic stop, and movement for each floor/direction according to the direction.
[0151] Though the forecasted trajectories in Fig. 33 are rough in shape, they are advantageous
in that the required number of data can be largely reduced because forecasted arrival
times on the highest floor and lowest floor in each round are only required. Therefore,
when one uses a microcomputer which is inexpensive but provides low processing performance,
it can be said that such a simple version of forecasted trajectories are effective.
[0152] When forecasted trajectory data (forecasted trajectory table) is recorded as a log
of allocation control contents each time a hall call allocation is performed, for
example, when a log of data for one week is to be recorded, an immense amount of data
will be recorded. In such an event, when the data is preserved in the form of the
forecasted trajectories as shown in Fig. 33, the amount of recorded data can be largely
reduced. It is also contemplated forecasted trajectories in detailed shape as shown
in Fig. 28 or 31 may be actually used for the control, while the forecasted trajectories
in Fig. 33 may be used for purposes of data preservation. In this event, the accuracy
of the forecasted trajectories is not degraded in the control, while the data of the
forecasted trajectories for preservation can be compressed. The data preserved/recorded
in this way can be relied on to analyze which trajectory was forecasted when the allocation
evaluation is checked at a later time, and is therefore effective. The configuration
of an embodiment for recording the forecasted trajectory data will be described later
with reference to Fig. 47.
[0153] Fig. 34 shows a sixth example of forecasted trajectories according to the forecasted
trajectory creation method shown in this embodiment. The forecasted trajectories shown
in Fig. 34 differs from the forecasted trajectories in Fig. 28 in that the forecasted
trajectories in Fig. 34 correspond to a higher floor zone (a zone of a plurality of
non-stop floors located in the middle).
[0154] Fig. 34(a) shows an example of a forecasted trajectory in a higher floor zone which
is created in accordance with the same way as Fig. 28. The left-hand diagram in Fig.
34(a) indicates a current cage position and direction, where a shaded area FN02 in
the diagram (eight floors from the first floor to the ninth floor) is designated to
be the higher floor zone. The forecasted trajectory for the elevator in the right-hand
diagram in Fig. 34(a) is a forecasted trajectory FN01 in the left-hand diagram in
Fig. 34(a). The stop probability is zero in the high floor zone because the elevator
is not stopped due to a call, so that the slope of the forecasted trajectory is a
steep and constant slope. The forecasted trajectory shown in Fig. 34(a) is an example
when all floors are shown.
[0155] On the other hand, Fig. 34(b) shows the section of the higher floor zone represented
by a single floor. Specifically, as shown in the left-hand diagram, the first to ninth
floors are represented by a single floor FN04. A forecasted trajectory in this event
is a trajectory FN03 in the right-hand diagram of Fig. 34(b). As shown, the forecasted
trajectory can be precisely represented even if the higher floor zone is represented
by a single floor, as long as a pass time of that zone is matched. The matching of
the zone pass time can be confirmed by the pass time of the higher floor zone in Fig.
34(a) which matches the pass time of the higher floor zone in Fig. 34(b).
[0156] One advantage of the forecasted trajectory as shown in Fig. 34(b) is a deletion of
redundant data. For example, in the shown example, information on the trajectory from
the first to ninth floors is redundant because any call is not generated therefrom.
Important areas are located in floors located on the upper and lower sides of the
higher floor zone, and a section of the trajectory in the important areas can be emphasized
by the representation of the trajectory, as done in Fig. 34(b), to evaluate the trajectory.
Also, since data on the first to ninth floors can be deleted, the data is effectively
compressed.
[0157] Fig. 35 shows a seventh example of the forecasted trajectories according to the creation
method shown in this embodiment. The forecasted trajectories in Fig. 35 differ from
the forecasted trajectories in Fig. 28 in that the forecasted trajectories in Fig.
35 are forecasted trajectories when respective elevator cars are assigned to services
of different floor zones. Specifically, a floor zone serviced by the first car extends
over all floors from B1 floor to thirteenth floor, as shown in the leftmost diagram
FP03, while a floor zone serviced by the second car extends from the first floor to
the ninth floor, as shown in the second diagram FP04. In this way, even when the respective
cars service different floor zones, the resulting forecasted trajectories reflect
the floor zones serviced by the respective cars, as represented by the forecasted
trajectories on the rightmost diagram. Specifically, the forecasted trajectory of
the first car is a trajectory FP01, and the forecasted trajectory of the second car
is a trajectory FP02.
[0158] The reason for the ability to create such forecasted trajectories lies in the fact
that direction inversion floors are identified for each car in the flow chart of the
forecasted arrival time table calculation routine illustrated in Fig. 20. In the example
of Fig. 35, the first car inverts the direction on the B1 floor and thirteenth floor,
while the second car inverts the direction on the first and tenth floors. By thus
identifying the floors on which each car inverts the direction, forecasted trajectories
can be created so as to correspond to different service zones. As a result, it is
possible to create more precise forecasted trajectories in accordance with the characteristics
of the respective cars.
[0159] By now, the forecasted trajectory creation method (executed by the forecasted trajectory
calculation unit in Fig. 12), and examples of created forecasted trajectories have
been described in detail. The forecasted trajectory creation method according to this
embodiment is a creation method which copes with the realities (reflects the realities),
and as a result, can create a variety of highly accurate forecasted trajectories as
shown in Figs. 28 to 35. It is therefore possible to make allocations which more properly
control the cage interval (in consideration of the interval uniformity), properly
maintain the cage interval, and restrain a long waiting time with high evaluation
accuracy such as in interval evaluation between forecasted trajectories.
[0160] Figs. 36 to 38 show details on a forecasted interval value calculation process. In
the following, a method of calculating a forecasted interval value will be described
with reference to a flow chart of Fig. 36. First, a phase time value tp of each cage
at an interval evaluation time tref is calculated using a forecast route of each cage,
the creation method of which has been previously described (ST801 in Fig. 36). Here,
the interval evaluation time tref has been set by the previously described setting
method. The calculation of the phase time value of each car will be described in greater
detail with reference to Figs. 37, 38.
[0161] Fig. 37 shows how the forecasted interval value is calculated from a forecast route.
Here, Fig. 37 shows a group management for three elevators, where the left-hand diagram
in Fig. 37 shows the positions and directions of elevator cages at a current time
point in a ring representation. From the left-hand diagram in Fig. 37, the first car
610 is moving between the sixth floor and seventh floor in the upward direction, and
the second car 611 is moving between the fourth floor and fifth floor in the upward
direction. The third car 612 in turn is moving downward from the second floor to the
first floor. The right-hand diagram in Fig. 37 represents forecasted routes of the
respective cages, where the horizontal axis indicates the time, and the vertical axis
indicates the position. The origin of the time axis represents the current time point.
A cage position 600 of the first car, a cage position 601 of the second car, and a
cage position 602 of the third car at the current time point are indicated, respectively,
on the diagram (a forecasted route 603 of the first car, a forecasted route 604 of
the second car, and a forecasted route 605 of the third car). The cage position at
the interval evaluation time tref (606 in Fig. 37) can be forecasted from the forecasted
route of each cage. For example, a forecasted position and direction of the first
car at the interval evaluation time tref are the sixth floor and upward direction
(607 in Fig. 37); a forecasted position and direction of the second car are the third
floor and upward direction (609 in Fig. 37); and a forecasted position and direction
of the third car are the fifth floor and downward direction (608 in Fig. 37). Forecasted
intervals between the respective cages can be found from such the forecasted positions
and directions of the respective cages.
[0162] Fig. 38 shows a process of finding a forecasted interval. The left-hand diagram in
Fig. 38 indicates the forecasted positions and directions of the three cages at the
interval evaluation time tref shown in Fig. 37. The right-hand diagram in Fig. 38
indicates a phase time value on the horizontal axis, and the position on the vertical
axis. Here, the phase time value refers to a time value normalized by a time of one
round (same as the period) (refers to a time value having a similar meaning to the
phase). This phase time value is calculated on the basis of an average round trajectory
(703 on the right-hand diagram in Fig. 38) for a traffic flow at a current time point.
By mapping the forecasted position of each cage indicated on the left-hand diagram
in Fig. 38 onto the average round trajectory, the forecasted position can be converted
to a phase time value. For example, a time phase value of the first car 705 can be
found as tp (k=1) from the average round trajectory 703 in Fig. 38. In a similar manner,
a time phase value of the second car 704 can be found as tp (k=2), and a time phase
value of the third car 706 can be found as tp (k=3). In this way, the reason for converting
from a forecasted position to a time phase value lies in that intervals between the
respective cages are expressed by time interval values in units of times.
[0163] A time phase value is found from the forecasted position of each cage (ST801 in Fig.
36), and then, the respective cages are sorted in an order according to the magnitude
of the phase time value (ST802 in Fig. 36). For example, in the case of Fig. 38, the
magnitudes of the phase time values of the respective cages are in the following relationship:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0015)
[0164] Accordingly, when a label variable indicative of the rank is represented by m, m=1
is satisfied by the second car; m=2 by the first car; and m=3 by the third car.
[0165] A forecasted interval value Bm between the respective cages is found in accordance
with the order of rank m of this phase time values (ST803). For example, in the case
of Fig. 38, the forecasted interval time between the cages of m=1 and m=2 is Bm=1
(corresponding to an interval value in a section 707 in Fig. 38); and the forecasted
interval time between the cages of m=2 and m=3 is Bm=2 (corresponding to an interval
value in a section 708 in Fig. 38). Likewise, the forecasted interval value between
the cages of m=3 and m=1 is Bm=3 (corresponding to an interval value in a section
709 in Fig. 38). The respective forecasted interval values are represented by the
following equations:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0018)
Where T in Equation (18) represents the period of an average round trajectory.
[0166] In the foregoing manner, the forecasted interval of each cage is calculated using
the phase time value based on the average round trajectory for the traffic flow at
the current time point, so that a more proper time interval can be found in accordance
with a traffic flow at a particular time. For example, at the start of a lunch time,
a large number of hall calls are generated for the downward direction, resulting in
the average round trajectory which has a slow slope of a line segment toward the downward
direction, and a longer phase time value per floor as compared with a line segment
toward the upward direction. Therefore, when two cages are spaced apart, for example,
by two floors, an evaluation is made to result in different interval values for the
upward direction and downward direction. Since cages going downward are more likely
to stop, they are evaluated to be more spaced even on the same first floor. In this
way, the time interval can be properly evaluated in accordance with the traffic flow.
[0167] Fig. 39 compares trajectories of elevator cages on the time axis in an scenario of
a group management for three cars between the result before the implementation of
the control according to this embodiment and the result after the implementation of
the control according to this embodiment. Fig. 39(a) shows trajectories of the elevator
cages on the time axis before the implementation of the control according to this
embodiment. It can be seen from these trajectories that the trajectories of the three
cars often overlap, showing the occurrence of a low-efficient bunch operation.
[0168] On the other hand, Fig. 39(b) shows trajectories of the elevator cages on the time
axis after the implementation of the control according to this embodiment. It can
be seen that the trajectories of the three cages maintain equal phases, just like
a three-phase alternate current, i.e., a temporally equidistant state. In this way,
since the temporally equidistant state can be maintained, an elevator cage can immediately
arrive in response to a hall call which is generated on whichever floor and in whichever
direction, thus making it possible to restrain a long waiting time.
[0169] Now turning back to Fig. 17, a description will be made of another exemplary configuration
of the cage interval evaluation value calculation unit 4 shown in Fig. 2. The configuration
in Fig. 17 is intended to evaluate a cage interval from a deviation between a target
route and a forecasted route (forecasted trajectory) with reference to the target
route (target trajectory) which is an ideal route (trajectory) in a temporally equidistant
state. The use of this target route is a feature of the configuration illustrated
in Fig. 17.
[0170] While the target route will be described later in greater detail, the configuration
of Fig. 17 can evaluate each cage interval uniformity over a wide time region because
the target route serves as a detailed reference for a higher time interval uniformity.
[0171] First, a target route creation unit 410 create an ideal route in a temporally equidistant
state for each cage based on input information (entered from the input information
storage unit 2 in Fig. 2), and a forecasted route creation unit 411 creates a forecasted
route for each cage. A method of creating the forecasted route is the same as the
previously described method, and the creation of the target route will be described
later with reference to Figs. 42 to 44. A route deviation calculation unit 414 calculates
a deviation of the forecasted route from the target route for each cage. This deviation
can be calculated, for example, using the area of a difference between the two routes.
A cage interval evaluation value calculation unit 415 calculates a cage interval evaluation
value (cage interval evaluation value when each cage is preliminary allocated to a
hall call) for each cage based on the calculated inter-route deviation. Based on the
cage interval evaluation values, a hall call is allocated to the cage having the highest
evaluation value. An average round time calculation unit 412 calculates an average
round time based on the input information, and an adjusted reference time setting
unit 413 determines the value of an adjusted reference time based on the average round
time T. The set adjusted reference time is used during the creation of the target
route. The creation of the target route will also be described later in greater detail
with reference to Figs. 42 to 44.
[0172] In the following, the allocation evaluation control based on the target route (one
of evaluation functions for a future call), shown in Fig. 17, will be described in
greater detail. As has been previously described in connection with Fig. 17, the allocation
evaluation control based on the target route comprises three fundamental components,
i.e., the target route creation unit 410, forecasted route creation unit 411, and
inter-route deviation calculation unit 412.
[0173] First, an operational concept of the target route control (control principles) will
be described with reference to Figs. 40, 41. Fig. 40 includes diagrams showing an
example of the control concept of the target route control. In Fig. 40, the left-hand
diagram is a diagram conceptually showing cross-sections of elevator paths (vertical
direction) within a building, and the states of elevator cars moving therein. The
right-hand diagram indicates the time axis on the horizontal axis (A01), and the axis
of floors of the building on the vertical axis (A02), where trajectories of the operations
of the respective elevator cages are represented on the time axis (generally called
the operation diagram). The diagram shows a situation of the elevator group management
for two cars by way of example. From the left-hand diagram, a first car (cage designated
by 1) has inverted the direction on the ground floor and is operating toward the upward
direction, wile a second car (cage designated by 2) is operating toward the downward
direction from the first floor. When this situation is seen in the right-hand operation
diagram, it can be seen that in the left direction from an axis (A02) indicative of
a current time point, both the first car (A03) and second car (A04) are operating
toward the downward direction, and are positioned on the ground floor and first floor,
respectively. In other words, in the right-hand operation diagram, a trajectory of
each elevator cage on the left side of the current time point represents an actual
trajectory. For example, the actual trajectory of the first car is a trajectory A031,
and the actual trajectory of the second car is a trajectory A041.
[0174] A key to this embodiment is trajectories drawn on the time axis in the future on
the right side of the current time point. They represent "target trajectories" which
should be traced by the respective cages. In the following, the target trajectory
is called the "target route." A feature of the allocation control based on the target
route is that the operation of each elevator cage (more precisely, the allocation)
is controlled to follow the target route. Specifically, the target routes for the
respective cages are a target route A032 for the first car, and a target route A042
for the second car. The introduction of the target (or reference) trajectory which
should be traced by each car on the time axis into the control is a feature unique
to the present invention, which has not been found in the conventional group management
control.
[0175] Fig. 41 includes diagrams showing how the allocation of an elevator cage is determined
for a hall call in accordance with the target routes. Fig. 41 includes basically the
same diagrams, where the left-hand diagram shows the states of elevators on a vertical
section of elevator paths, and the right-hand diagram represents an operation diagram.
Assume first that a new hall call is generated on the second floor for an upward movement.
See the left-hand diagram of Fig. 41. In response to this hall call, the group management
control allocates an appropriate car from the first car (B03) and second car (B04).
Here, note movements of the first car (BD3). The target route of the first car is
a trajectory B032. Forecasted route of the first car (forecasted trajectory in the
future from the current time point. This forecasted trajectory is hereinafter called
the "forecasted route") is a route B033 (forecasted route 1) when the first car is
allowed to pass without allocated a new hall call. Therefore, when a new hall call
is allocated to the first car, a route B034 (forecasted route 2) is employed instead.
Here, in the group management control of this embodiment, movements of each car are
moved to follow the target route. As such, the forecasted route 1 B033 is closer to
the target route, i.e., the route on which the first car is allowed to pass without
allocated a hall call, so that the first car is not allocated any hall call. As a
result, the actual trajectory of the first car operates to follow the target route.
[0176] According to the control based on the target route, the target route is drawn such
that each elevator cage follows a temporally equidistant trajectory in the future.
In this way, the actual trajectory of the cage follows its target route, and as a
result, each cage can be controlled to maintain the temporally equidistant trajectory
with stability for a long term. For example, in the case of Fig. 41, it can be seen
that the actual trajectories of the fist car (B03) and second car (B041) up to the
current time point, i.e., the trajectory (B031) of the firs car and the trajectory
(B041) of the second car are close to each other, and therefore, they are in a bunch
operation state. Here, if a new hall call generated on the third floor in the upward
direction is allocated to the second car, the distance between the first car (B03)
and second car (B04) still remain close to each other, and the bunch operation continues.
However, when the first car and second car are separated away from each other and
controlled to follow the target routes which are set to make the respective trajectories
temporally equidistant, the first car (B03) is not allocated, and following the target
routes, they approach to the temporally equidistant state.
[0177] In the following, the feature of the control principles of the elevator group management
system according to this embodiment will be summarized with reference to Figs. 40
and 41.
- 1) As shown in Fig. 40, a target trajectory on the time axis, i.e., a target route
is set for each cage.
- 2) As shown in Fig. 41, the target route and forecasted route are compared, and the
allocation of a hall call is determined to a cage which more approaches to the target,
such that the trajectory of each cage follows the target route.
- 3) As a result, each cage operates to follow the target route.
- 4) Here, the target route is basically set such that the trajectory of each cage becomes
temporally equidistant, so that each cage is controlled to be in a temporally equidistant
state with stability for a long term.
[0178] Fig. 42 shows an outline of a target route creation process. Fig. 42 shows a target
creation process which utilizes an adjustment area (later described). A graph D01
indicates the time on the horizontal axis, and floor positions in a building on the
vertical direction, with a current time point defined at the origin (D03) of the time
axis. While no graph is drawn in Fig. 42, a target route, as shown in Fig. 43, will
be drawn therein by way of example.
[0179] Fig. 43 shows an example of target route shapes before and after an adjustment according
to one embodiment of the present invention. A target route creates a route to accomplish
a temporally equidistant state at a predetermined time in the future, and this predetermined
time corresponds to an adjusted reference time axis D04. The target route is represented
by a route which represents a transient state until the temporally equidistant state
prevails in an area between the time axis D03 at the current time point and the adjusted
reference time axis D04 (called the "adjustment area"), and is represented as a route
which enters the temporally equidistant state after the adjusted reference time axis
D04.
[0180] Such a target creation process is composed of the following four processes.
- 1) A forecasted route at a current situation is drawn (ST701 in Fig. 42).
- 2) The phase time value of each cage in the current situation on the adjusted reference
time axis is calculated (ST702).
- 3) The amount of adjustment is calculated for each cage, based on the phase time value
in the current situation, so as to accomplish the temporal equidistance (ST703).
- 4) A grid of the forecasted route within the adjustment area is adjusted in accordance
with the amount of adjustment, and this is used for a target route (ST704).
[0181] Fig. 44 shows an example of the configuration of the target route creation unit.
The configuration of the illustrated target route creation unit is generally composed
of the following four components:
- 1) a target route update determination unit 103A;
- 2) a current phase time value calculation unit 103B;
- 3) an adjustment amount calculation unit 103C for the phase time value of each cage;
and
- 4) an adjusted route creation unit 103D.
[0182] First, a control concept will be described in terms of actions of the foregoing four
components. The target route update unit 103A determines whether or not a current
target route should be updated. When it is determined that the target route should
be updated, the current phase time value calculation unit 103B at the next stage evaluates
an interval state of the route of each cage with an index called a "phase time value"
for a forecasted route of each elevator cage at that time point. The reason for the
use of the concept of "phase" is based on the fact that when the waveform of a three-phase
alternate current of a sinusoidal wave is considered in the electric circuit theory,
for example, a state in which the phases of the respective phases are uniformized
is a state in which the phase of each phase is in an equal phase state by 2π/3(rad)
each. In other words, when the route of each cage is regarded as a waveform, and a
"phase-like index" is used for the waveform, an interval state for each route is readily
evaluated. This "phase-like index" corresponds to the index called the "phase time
value" used in this embodiment. The phase time value will be described later. After
the current phase time value calculation unit 103B has calculated the phase time value
at that time point, a phase time value adjustment amount for each cage is calculated
in the adjustment amount calculation unit 103C for the phase time value of each cage
in order to make the phase time value uniform. Based on the adjustment amount calculated
above, the adjusted route creation unit 103D adjusts the time phase value of the original
forecasted route 103B of each cage. The route resulting from the adjustment serves
as a target route.
[0183] The operation for the general control configuration described above will be described
with reference to an operational concept in Fig. 43. Fig. 43 is an operational conception
diagram of a target route creation process executed by the target route creation unit
shown in Fig. 44. Described herein first is the operational concept of the control
based on the previously described general control contents. First, the diagram (target
route shape before the adjustment) of Fig. 43(a) corresponds to a forecasted route
of each cage at a current time point which is based to create a target route. Here,
an elevator group management system for three cars is considered. In Fig. 43(a), a
cage C010 of a first car, a cage C020 of a second car, and a cage C030 of a third
car are descending the eighth floor, descending the second floor, and descending the
third floor, respectively, on a axis C050 at the current time point. Forecasted routes
(forecasted trajectories) of the three cages subsequent to the current time point
are indicated by a solid line trajectory C011 for the first car, a one-dot chain line
trajectory C031 for the second car, and a dotted-line trajectory C031 for the third
car, respectively. In this connection, a forecasted route creation method will be
described in detail in a section of a description of the forecasted route creation
unit. These trajectories are apparently close to one another, from which it is understood
that the three cages are close to a bunch operation state. Turning back to the control
configuration of the target route creation unit in Fig. 44, first, when the target
route update determination unit 103A determines an update of target routes, the current
phase time calculation unit 103B regards the forecasted routes C011, C021, C031 of
the respective cages in Fig. 43(a) as one type of waveforms, and calculates their
respective phase time values. The phase time values are calculated at intersections
at which an adjusted reference time axis C040 in the diagram of Fig. 43(a) intersects
the forecasted routes of the respective cages. Next, based on the phase time values,
the adjustment amount calculation unit 103C for the phase time value of each cage
calculates the amounts of adjustment for the respective forecasted routes to be in
an equidistant state. The amounts of adjustment are represented as three black circular
points on the adjusted reference time axis C040 in Fig. 43(a). For example, in regard
to the first car, a point C01A is a point which reflects the amount of adjustment,
and the forecasted route C011 of the first car is adjusted in the next processing
to pass this point C01A. Likewise, a forecasted route C021 of the second car is adjusted
in the next processing so as to pass a point C02A, and a forecasted route C032is adjusted
in the next processing so as to pass a point C03A. It is the adjusted route creation
unit 103D in Fig. 44 that performs this adjustment processing, and the forecasted
routes are adjusted on the basis of the amounts of adjustment to create new target
routes. The results are the trajectories shown in Fig. 43(b). Fig. 43(b) is a diagram
showing new target routes which are created on the basis of the forecasted routes
shown in Fig. 43(a). For the three cages C010, C020, C030, a target route of the first
car C010 is a solid line trajectory C011N, a target route of the second car C020 is
a one-dot chain line trajectory C021N, and a target route of the third car C030 is
a dotted line trajectory C031N . A feature of the trajectories of the target routes
lies in that the route of each cage is drawn so as to guide to the temporally equidistant
state, as shown in Fig. 43(b). Specifically, in Fig. 43(b), the target routes of the
three cages are in the temporally equidistant state, respectively, after the adjusted
reference axis C040. In a time period between the axis C050 indicative of the current
time point and the adjusted reference time axis C040 (a time area labeled the "adjustment
area" in Fig. 42), the trajectory is drawn such that each cage is guided to such a
temporally equidistant state. Based on the forecasted routes shown in Fig. 43(a),
the respective routes are adjusted such that each route passes the point found with
the amount of adjustment, i.e., the point C01A, C02A, C03A on the adjusted reference
axis. In this way, the target routes can be created as shown in such Fig. 43(b).
[0184] In the following, the components in the target route creation unit illustrated in
Fig. 44 will be described in detail. The current phase time value calculation unit
103B comprises an initial state route creation unit 103B1, an adjusted reference axis
setting unit 103B2, a phase time value calculation unit 103B3 for calculating the
phase time value of each car on the adjusted reference axis, and a phase time value
order sorting unit 103B4. The initial state route creation unit 103B1 creates a forecasted
route for each cage at a particular time point for use as a route in an initial state.
This route in the initial state corresponds to the target route shape before adjustment
shown in Fig. 43(a). The adjusted reference axis setting unit 103B2 sets the adjusted
reference time axis. The phase time value calculation unit 103B3 for calculating the
phase time value of each axis on the adjusted reference axis calculates a phase time
value of each cage on the adjusted reference time axis. Specifically, the phase time
value is calculated for an intersection of the forecasted route of each cage with
the adjusted reference time axis (corresponding to a forecasted position of each cage
on the adjusted reference time axis). After calculating the phase time value of each
cage in the phase time value calculation unit 103B3 for calculating the phase time
value of each axis on the adjusted reference axis, the phase time value order sorting
unit 103B4 sorts the phase time values for the respective cages in the order of the
phase time value. In the following, this order is called the "phase order." For example,
giving as an example the cage state of three cars in the target route shapes before
the adjustment (corresponding to the forecasted routes) in Fig. 43(a), from the intersections
of the adjusted reference axis C040 with the forecasted routes C011, C021, C031 of
the respective cages, the order of the phase time values of the respective cages are
in the phase order of the third car, second car, and first car from the smallest one.
The phase time value order sorting unit 103B employs a sorting algorithm, for example,
a direct selection method, a bubble sort or the like to find such a phase order.
[0185] The adjustment amount calculation unit 103C for the phase time value of each cage
calculates the intervals between the respective cages using the phase time values
based on the calculated phase time values of the respective cages and the phase order
thereof, compares the values with a reference values for providing an equidistance,
and calculates the amount of adjustment for the phase time values of the respective
cages, as represented by the differences therebetween. Here, the concept is that the
intervals between the respective cages (evaluated by the phase time value) are found
from the forecasted routes, and they are compared with the reference value for providing
the equidistance, and the differences therebetween are used for the amount of adjustment
to be adjusted from there. Giving Fig. 43(a) as an example, a description will be
given of processing contents of the adjustment amount calculation unit 103C for the
phase time value of each cage. As described above, in Fig. 43(a), the phase order
of the phase time values on the adjusted reference time axis C040 of the forecasted
routes C011, C021, C031 of the respective cages is in the order of the third car,
second car, and first car. When one round time of the forecasted route is represented
by T (the three cars are equal in round time to one another), a phase time value tp(k)
of a k-th car is tp(3)=0.09 for the third car, tp(2)=0.17T for the second car, and
tp(1)=0.77T for the first car. Calculating the intervals between the respective cages
in the phase order, the interval between the second car and third car is 0.08T (tp(2)-tp(3));
the interval between the first car and second car is 0.6T (tp(1)-tp(2)); and the interval
between the third car and first car is 0.32T (tp(3)-tp(1)+T). In this way, by quantifying
the intervals between the respective cages using the phase time values, it is possible
to quantitatively evaluate the intervals between the respective cages. For example,
it is understood from the foregoing result that the interval between the second car
and third car is very close. Since one round time is designated by T in the phase
time value, the intervals between respective cages in the intended temporally equidistant
state can be represented by T/N in a group management for N cars. In the example of
Fig. 43(a), where three cars are intended for the group management, a target interval
between cages is T/3=0.33T. The difference between this target interval and the current
interval between the respective cages is an interval to be adjusted. For example,
between the second car and third car, +0.25T (=0.33T-0.08T) is an interval value to
be adjusted. Likewise, interval values to be adjusted are -0.27T(=0.33T-0.6T) between
the first car and second car, and +0.01T(=0.33T-0.32T) between the first car and second
car), respectively. In the foregoing, the positive sign represents an increase in
interval, where the current interval must be extended for the target. On the other
hand, the negative sign represents a decrease in interval, where the current interval
must be reduced for the target. Based on the interval values to be adjusted, the amount
of adjustment to the phase time value is adjusted for each cage. This can be found
in accordance with the following algorithm. For example, assume that in a group management
for three cars, an A-car, a B-car, and a C-car are arranged in this order. For generalizing,
the names of cars are given in alphabet. From the foregoing, 0≦tp(A)≦tp(B)≦tp(C)<T
is established. Here, the amount of adjustment to the phase time value for each car
is represented by Δtp(k) (k indicates that a cage is a k-th car). First, the following
equations must be established in order to satisfy an interval of T/3 which is the
target of adjusted intervals of the respective cages:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0021)
[0186] For example, with respect to Equation (19), the adjusted phase time value is represented
by tp(B)+Δtp(B) for the current phase time value tp(B). As such, Equation (19) represents
that the difference between the adjusted phase time value of the B-car and the adjusted
phase time value of the A-car, i.e., the interval satisfies T/3. Here, since the three
equations are not independent of one another, Δtp(A), Δtp(B), Δtp(C) cannot be solved
with the three equations alone. Thus, another condition is added that a positional
barycenter as viewed in the current phase time value of each cage matches a positional
barycenter as viewed in the adjusted phase time value of each cage. This condition
is represented by the following equation:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0022)
[0187] Equation (22) is arranged to derive Equation (23) :
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0023)
[0189] In conclusion, for three cages A-car, B-car, C-car which have the phase time values
that satisfy 0≦tp(A)≦tp(B)≦tp(C)<T, it is possible to find the amounts of adjustment
Δtp(A), Δtp(B), Δtp(C) which are at equal intervals after adjustment, and satisfy
the condition that the positional barycenters of the three cars do not change. These
amounts of adjustment Δtp(A), Δtp(B), Δtp(C) can be calculated by Equations (24),
(25), (26), respectively. For example, giving Fig. 43(a) as an example, The A-, B-,
C-cars are the third, second, first cars, respectively. Therefore, tp(A)=tp(3)=0.09T,
tp(B)=tp(2)=0.17T, and tp(C)=tp(1)=0.77T. Accordingly, the amounts of adjustment to
the respective cages are calculated by Equations (24) - (26) as Δtp(A)=Δtp(3)=-0.081T,
Δtp(B)=Δtp(2)=0.177T, and Δtp(C)=-0.096T. For confirmation, the respective phase time
values are calculated after the adjustment:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0028)
and
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0029)
[0190] Stated another way, the intervals between the respective cages are 0.33T and can
therefore satisfy the condition for the equal intervals.
[0191] Next, a detailed description will be given of a process for creating an adjusted
route by the adjusted route creation unit 103D using the amounts of adjustment calculated
by the adjustment amount calculation unit 103C for the phase time value of each cage.
In the adjusted route creation unit, an adjustment amount calculation unit 103D1 for
a grid on the route of each cage calculates the amount of adjustment to a grid on
the target route before adjustment (corresponding to the forecasted route) of each
cage. The grid is defined to be a direction inversion point of the route intended
in the adjustment area. By adjusting the position of the grid in the horizontal direction,
it is possible to adjust the phase time value of the route of interest. The amount
of adjustment to each grid is determined by a method of assigning from a grid close
to a current time point in order to a value which exceeds a limiter value set for
that grid, with the amount of adjustment to the cage as a total amount. Here, the
limiter value for the amount of adjustment to each cage is set by a grid limiter value
setting unit 103D2. An adjusted grid position calculation unit 103D3 calculates a
grid position gp_N(k, i) after the adjustment from the amount of adjustment Δgtp(k,
i) to each grid and the position gp(k, i) of the grid before the adjustment. For example,
with k=second car, and the number of grid equal to three (i=1, 2, 3), equations of
the respective grids are as follows:
![](https://data.epo.org/publication-server/image?imagePath=2007/13/DOC/EPNWA1/EP06019811NWA1/imgb0032)
[0192] The amount of adjustment to a grid is taken over to subsequent grids, so that the
last grid is adjusted in position by the total amount of adjustment to the phase time
value for an associated cage. In the foregoing manner, a new target route can be created
by connecting the positions of the respective adjusted grids. A target route data
calculation unit 103D4 calculates and updates new target route data.
[0193] A newly updated target route (adjusted target route) passes an adjusted target point
set to the amount of adjustment to the phase time value. Since the route of each cage
is adjusted to pass the adjusted target point, the result of collecting the three
cars is as shown in Fig. 43(b), from which it can be seen that the target routes C011N,
C021N, C031N of the three cars are in a temporally equal interval state. Of course,
each route C011N, C021N, C031N passes the respective adjusted target point C01A, C02A,
C03A. It can be also seen that the target route within the adjustment area adjusted
by the grid plays an role of a transient guide for accomplishing the temporally equal
interval state after the adjusted reference time axis. The foregoing is a detailed
description on the target route creation process.
[0194] Fig. 45 illustrates a second embodiment which is different from Fig. 2 of control
blocks in the overall elevator group management system according to the present invention.
In Fig. 45, components identical to those in Fig. 2 are designated the same reference
numerals, and a description thereon is omitted here. Fig. 45 differs from Fig. 1 in
that the weighting coefficient is directly determined from the number of generated
hall calls. Specifically, a hall call count calculation unit 10 calculates the number
of generated hall calls, and based on this, a weighting coefficient calculation unit
5 calculates the weighting coefficient directly from the number of generated hall
calls.
[0195] Fig. 46 shows an example of a function for use by the weighting coefficient calculation
unit 5 for finding the weighting coefficient. In Fig. 46, the horizontal axis indicates
the number of hall calls generated per round, and the vertical axis indicates the
weighting coefficient. Here, the number of hall calls generated per round refers to
an average number of hall calls which are generated during one round (for example,
from the lowest floor in the upward direction to the lowest floor in the downward
direction) of each of elevators which are managed in group.
[0196] In Fig. 46, the function for determining the weighting coefficient is represented
by a curve F04. This function has the following four features.
- 1) The function can immediately find an appropriate value of the weighting coefficient
from the number of generated hall calls.
- 2) the value of the weighting coefficient, which is the output, is continuously determined
following a continuous change in the number of hall calls generated per round, which
is an input variable.
- 3) The input variable is a scalar value (one variable).
- 4) The input variable can continuously take values as real numbers.
[0197] From the graph of Fig. 46, when the number of hall calls generated per round is NA,
for example, the weighting coefficient is WT=F(NA). Irrespective of how NA changes
due to a change in traffic demand, WT can be immediately determined. This constitutes
a large feature. Also, the weighting coefficient value is always zero for a value
on the horizontal axis at which the zero value on the vertical axis intersects.
[0198] As previously described, the reason for which the appropriate weighting coefficient
can be found by specifying the number of hall calls generated per round of an elevator
lies in that the importance of the interval evaluation value is strongly related to
the number of hall calls possibly generated in the future. For example, as a larger
number of hall calls are generated in the future, the interval should be made as temporally
even as possible, so that the interval evaluation value should be forced to more strongly
act. Here, it is assumed that the number of hall calls possibly generated in the future
has a high correlation with the number of hall calls generated per round at a particular
time point or a time point subsequent thereto. Therefore, a certain relationship is
established between the number of hall calls generated per round and an appropriate
weighting efficient value, and by representing this as functions as shown in Fig.
10, an appropriate weighting coefficient can be determined from the number of hall
calls generated per round of the elevator.
[0199] It should be noted that the graph in Fig. 46 shows an example in which the horizontal
axis indicates the number of hall calls generated per round, but may indicate, not
limited to this, a value based on the number of generated hall calls, for example,
the number of hall calls generated for a predetermined time. Further alternatively,
the horizontal axis may indicate an index of a scalar value related to traffic demand,
not limited to the number of generated hall calls. For example, the horizontal axis
may indicate the number of users, or a value based on the total value of the number
of generated hall calls and the number of generated cage calls.
[0200] From the foregoing, the configuration of Fig. 45 is advantageous over the configuration
of Fig. 2 in that an appropriate weighting coefficient can be promptly set by a simpler
configuration. As a result, stable performance can be maintained even using a microcomputer,
a processor, or the like which is expensive but provide low processing capabilities.
[0201] Fig. 47 illustrates a third embodiment which is different from Figs. 2 and 45 of
the elevator group management systems according to the present invention. In Fig.
47, components identical to those in Fig. 2 are designated the same reference numerals,
and a description thereon is omitted. Fig. 47 differs from Fig. 2 in that an assignment
evaluation information display processing unit H01 is additionally provided. This
assignment evaluation information display processing unit H01 is characterized by
recording internal information such as an evaluation value which is relied on to determine
an allocation of a hall call, intermediate information thereof, and the like, displaying
the contents as required, transferring to the outside, and recording them on a recording
medium. The purposes are to analyze, for each allocation process, which factor caused
the allocation, and to reveal, when a long waiting occurred, for example, in which
situation the long waiting was reached. Particularly, such a display processing means
is effective because the elevator group management system according to the present
invention can visually indicates the will of the group management control side through
forecasted trajectories and target routes.
[0202] In the following, the configuration of the allocation evaluation information display
processing unit H01 will be described. The allocation evaluation information display
processing unit H01 is composed of a determination unit H02, a recording unit H03,
a drawing processing unit H04, a recording medium H05, and an output unit H06. The
determination unit H02 is a component for determining whether or not evaluation value
information should be recorded, and is configured to record information on allocation
variation in the recording unit H03 when a recording enable signal is generated from
the determination unit H02. This determination may involve, for example, a particular
time zone, a particular traffic flow, the occurrence of an average waiting time equal
to or larger than a predetermined value, and the occurrence of an average hall call
continuation time equal to or larger than a predetermined value. The recording unit
H03 records variety of data associated with the allocation evaluation calculated by
the group management control unit 1. For example, the recording unit H03 records a
waiting time evaluation value calculated b the waiting time evaluation value 3, the
output of the cage interval evaluation calculation unit 4, the weighting coefficient
set by the weighting coefficient setting unit 8, the output of the general evaluation
value calculation unit 6, and the name of car to which an allocation is determined,
which is the output of the allocated elevator determination unit 7. For the cage interval
evaluation value calculation unit 4, its detailed functions have been shown in Fig.
48, and will be described later in greater detail. The drawing processing unit H04
performs a drawing data creation process for drawing information related to allocations
recorded in the recording unit H03 on a screen. The output unit H06 displays drawing
data on the screen. The recording medium H05 preserves data recorded by the recording
medium H03. The recording medium H05 used herein may be a floppy disk, a memory card,
a USB memory, a hard disk or the like. The drawing data created by the drawing processing
unit H04 is transferred to the outside through a communication network H07, so that
the drawing data can be remotely displayed on a screen or recorded.
[0203] Fig. 48 is a detailed functional block diagram of the interval evaluation value calculation
unit 4, showing the flow of data information recorded by the recording unit H03. The
configuration of Fig. 48 is based on Fig. 12, so that components identical to those
in Fig. 12 are designated the same reference numerals, and a description thereon is
omitted here. Data sent to the recording unit H03 includes the interval evaluation
time tref calculated by the interval evaluation time setting unit 405, which is outputted
from an interval evaluation time data output unit 4Z2. Further, there is forecasted
car trajectory data (specifically, the forecasted trajectory table of Fig. 23) created
by the forecasted trajectory calculation unit 401, outputted by a forecasted trajectory
data output unit 4Z3. Since the forecasted trajectory data is large in amount as it
is, it may be converted, for example, to a simple version of forecasted trajectories
as shown in Fig. 33 to compress the data amount, and can therefore be limited to an
appropriate data amount. Such a conversion process is performed by a forecasted trajectory
data conversion unit 4Z1. Otherwise, forecasted cage interval data calculated by the
forecasted cage interval processing unit 402 (outputted from an output unit 4Z5),
interval evaluation value data calculated by the interval evaluation value calculation
unit 403 (outputted from an output unit 4Z6), and the like are outputted to the recording
unit H03 for recording.
[0204] Fig. 49 shows an example of screen output data created by the drawing processing
unit H04 and displayed by the output unit H06 in Fig. 47. Screen output elements in
Fig. 49 can be generally classified into the following four groups:
- 1) a group L001 for displaying information related to forecasted trajectories;
- 2) a group L002 for displaying information related to a hall call intended for allocation;
- 3) a group L003 for displaying evaluation value information; and
- 4) a group L004 for displaying detailed information on interval evaluation values.
[0205] In the following, the respective groups will be described in detail.
[0206] First, the group L001 for displaying information related to forecasted trajectories
is characterized by collectively displaying the following data on a graph L006 which
represents the time and floor positions on the two axes. Data displayed on the graph
may include forecasted trajectories of respective cars (a forecasted trajectory L010
of a first car, and a forecasted trajectory L011 of a second car), an interval evaluation
time L012, and cage positions of the respective cars at an interval evaluation time
(a cage position L015 of the first car and a cage position L016 of the second car).
Such a display can show in detail how the forecasted trajectory of each car is like,
at which time point a cage interval of each car is evaluated, and how the positional
relationship between the cages are like at that time. As a result, how the cage interval
evaluation has acted can be visually and readily confirmed together with the cage
interval evaluation value, later described. Particularly, in the present invention,
the interval evaluation time is adaptively adjusted in accordance with a situation
of call making and a situation of traffic flow, so that it is important to explicitly
display which time point was selected to be the interval evaluation time in the event
of that allocation. In addition, an upper left drawing L005 (a cage L007 of the first
car, a cage L008 of the second car, and a hall call L009), which displays a cage state
and a call state at the allocation time, is displayed. They are effective in supporting
information on the forecasted trajectories. For example, it is possible to understand
a basis of a forecasted trajectory drawn from which call occurrence state.
[0207] Next, the group L002 for displaying information related to a hall call intended for
allocation displays time information L017 on a time at which the hall call was generated,
hall call floor information L018, and hall call direction information L019. Details
on the hall call intended for allocation can be confirmed from these pieces of information.
[0208] The group L003 for displaying evaluation value information displays each information
of an allocated car name L020, waiting time evaluation value L021 at a particular
time point, a cage interval evaluation value L022, a weighting coefficient value L023,
and a general evaluation value L024. All these pieces of information are important
information which plays an important role in determining the allocation, and by displaying
them one by one, it is possible to know from which factor the allocation was determined.
In other words, the factor of determining the allocation can be roughly estimated
from the information displayed in the group L003 which displays evaluation value information.
For example, the waiting time evaluation value strongly acted in order to avoid a
long waiting time, an exacerbation of the cage interval evaluation value was avoided,
the weighting coefficient value was large at a certain time point so that the cage
interval evaluation value was regarded as important, and the like, which can support
a search for the allocation determination factor. Also, by displaying these pieces
of information together with the information of the group L001 which displays information
related to the forecasted trajectories, the contents of the cage interval evaluation
value, which is difficult to understand with numbers alone, can be more intuitively
understood.
[0209] The group L004 for displaying detailed information on the cage interval evaluation
value displays detailed information internal to a process calculated in calculating
the cage interval evaluation value. Specifically, information including an interval
evaluation time value L025, a forecasted cage position L026 of each car at the interval
evaluation time, and the forecasted cage interval L027 is displayed. Since the cage
interval evaluation value is information which aggregates all, the basis of being
an evaluation value can be hard to understand in a quantitative sense. In such an
event, a further detailed analysis can be made from the aforementioned detailed information.
[0210] The foregoing description has been made on an example of screen output data created
by the drawing processing unit H04 and displayed by the output unit H06 in Fig. 47.
A principal feature of the screen output data is that the forecasted trajectory of
each car, the interval evaluation time which is the time at which the cage position
is forecasted on the forecasted trajectory, the forecasted cage position and direction
of each car at the cage interval evaluation time are collectively displayed on a single
graph. Further, the screen output data features in that a waiting time evaluation
value of a car intended for allocation evaluation, a cage interval evaluation value,
a weighting coefficient value, and a general evaluation value are displayed in parallel
as evaluation value information. As a result of such a display, it is possible to
visually clearly demonstrate the forecasted trajectory of each car for allocation
of interest, a time point at which a cage interval is forecasted on the forecasted
trajectory, and the cage position at that time. It is therefore possible to display
in a readily understandable manner a situation (forecasting situation) which is based
on to evaluate the cage interval. For example, it is also possible to readily show
under which situation such an allocation was made for a user who is in doubt about
the basis of a certain allocation, by visually displaying the forecasted trajectory,
the time point of the forecast (interval evaluation time), and a forecasted cage position.
Also, since breakdowns of the evaluation value are shown, it is possible to readily
know which of the waiting time evaluation value and cage interval evaluation value
is a factor to result in determination of allocation. Considering that the waiting
time evaluation value is an evaluation value for an actual call which has been previously
generated, while the cage interval evaluation value is an evaluation value for a future
call which has not been generated, it can be said that these pieces of information
show which of the actual call and feature call was a factor that resulted in allocation.
In other words, a basic intention for the allocation can be known.
[0211] Fig. 50 shows an embodiment of display output data different from Fig. 49. In Fig.
50, elements identical to those in Fig. 49 are designated the same reference numerals,
and a description thereon is omitted here. Fig. 50 differs from Fig. 49 in that a
forecasted trajectory before hall call allocation (a forecasted trajectory L010 of
a first car), indicated by a solid line, is superimposed on a forecasted trajectory
after the hall call allocation (a forecasted trajectory L101 of the same first car),
indicated by a broken line, in the display. The forecasted trajectory L101 after the
hall call allocation includes a stop caused by the hall call allocation which appears
on the trajectory. Specifically, this is a horizontal trajectory section indicated
by reference numeral L102. In this connection, a hall call L009 at this time is generated
on the twelfth floor in the upward direction.
[0212] By superimposing the forecasted trajectories before and after the hall call allocation
in the display, as shown in Fig. 50, it is possible to more specifically display how
the cage interval changes due to the allocation. In the example of Fig. 50, the cage
interval extends to the forecasted trajectory L101 after the allocation of the first
car with respect to a forecasted trajectory L011 of the second car, indicated by a
one-dot chain line. In other words, the cage interval changes in a desired direction
in view of the cage interval evaluation. Particularly, since the cage intervals can
be compared before and after the allocation, the effect produced by the allocation
can be quantitatively displayed in a readily understandable manner. This is effective
in analyzing a factor of allocation and understanding the basis of allocation.
[0213] Fig. 51 shows a third example of the screen output data which is different from Fig.
49. In Fig. 51, elements identical to those in Fig. 49 are designated the same reference
numerals, and a description thereon is omitted here. Fig. 51 differs from Fig. 49
in that actual operation trajectories of respective cages before a time point at which
allocation was performed are displayed side by side together with forecasted trajectories
of the respective cars. Specifically, in Fig. 51, the actual operation trajectory
of the first car is represented by a trajectory L201 indicated by a solid line, and
the actual operation trajectory of the second car is represented by a one-dot chain
line L202. An allocation performed time point is on an axis L203. Centered on this
axis, the actual operation trajectories are displayed on the left side, and the forecasted
trajectories are displayed on the right side. In the actual trajectories, all stops
of the cages have actually occurred, and reference numeral L204 shown halfway on the
actual operation trajectory L201 of the first car indicates that the first car has
actually stopped on the second floor in the upward direction. In other words, no probabilistic
stop exists. This is an apparent difference between the actual operation trajectory
and forecasted trajectory.
[0214] By displaying the forecasted trajectories together with (in connection with) the
actual operation trajectories before the time point at which the allocation is made
for the respective cars as shown in Fig. 51, changes in the interval between the respective
cages before the allocation can be seen in comparison with future forecasts. As a
result, it can be seen, for example, that a bunch operation state has so far prevailed,
but an action is taken to avoid the bunch operation with the aid of the forecasted
trajectories, or on the contrary, that a temporally equal interval state has so far
prevailed, but is gradually approaching to a bunch operation in the future, as can
be seen from the forecasted trajectories. Therefore, it can also be confirmed that
an allocation is intentionally performed to space apart for protection in order to
avoid this.
[0215] From the foregoing, by displaying the forecasted trajectories together with (in connection
with) the actual operation trajectories as shown in Fig. 51, changes in the cage interval,
as viewed on the time axis, can be shown in a readily understandable manner. Also,
a situation in which the cage interval is changing, and past particulars can be readily
understood to more readily analyze a factor of allocation.
[0216] Fig. 52 illustrates an example of a processing flow of a forecasted trajectory display
method. This example assumes a method of displaying a forecasted trajectory for each
preliminarily allocated car. The flow of the process will be described below in a
specific manner. First, necessary data is read (L301), and a display format is next
selected (L302). This selection of the display format can involve, for example, a
selection of items to be displayed, and a setting of a range for a display time. Next,
a hall call to be displayed is selected (L303). Next, a variable K indicative of a
preliminary allocated car is initially set to one (K=1) (L304). Subsequently, display
data (A) on a forecasted trajectory of a K-th car when the K-th car is preliminarily
allocated to the selected hall call is created (L305). Further, display data (B) on
each car other than the K-th car is created (L306). Next, display data (C) on an interval
evaluation time is created (L307). After the completion of the foregoing processing,
a screen which is a combination of the foregoing (A), (B), (C) is stored as a display
or a data, as image data of the forecasted trajectory of each car when the K-car is
preliminarily allocated to the hall call (L308).
[0217] Next, K is incremented by one (L309), the foregoing process is repeatedly executed
for the next car, and is repeated until it has been executed for all cars (L310).
By performing such a process, the display screen data described in connection with
Figs. 49 - 51 can be created.
[0218] Fig. 53 illustrates an example of a processing flow of the forecasted trajectory
display method, which is different from Fig. 52. This example shows a method of displaying
a forecasted trajectory of a car to which a call is allocated. The flow of the process
will be described below in a specific manner.
[0219] First, necessary data is read (L401), and a display format is next selected (L402).
This selection of the display format can involve, for example, a selection of items
to be displayed, and a setting of a range for a display time. Next, a database which
records hall calls which have been generated in the past is searched for a hall call
H to be displayed (L403). Next, a past database is searched for a K-th car which is
determined to be actually allocated to the retrieved hall call H (L404). Subsequently,
display data (A) on a forecasted trajectory of the K-th car, when the selected hall
call is allocated to the K-th car, is created (L405). Further, display data (B) on
a forecasted trajectory of each car other than the K-th car is created (L406). Further,
display data (C) on an interval evaluation time is created (L407). After the completion
of the foregoing process, a screen which is a combination of the foregoing (A), (B),
(C) is stored as a display or a data, as image data of the forecasted trajectories
of the allocated car (K) for the hall call and other cars (L408). By performing such
a process, the display screen data can be created as shown in Fig. 49 - 51.
[0220] According to the embodiment described above, by providing forecasted trajectory creating
means for creating a forecasted trajectory indicative of a movement of a forecasted
position of each elevator on a time axis for a predetermined period from a current
time point to a near future, and forecasted trajectory display means for displaying
the forecasted trajectory of each car, a factor of allocation evaluation can be analyzed
from a more macroscopic view in the allocation evaluation for controlling the respective
cages to be arranged at equal intervals.
[0221] Also, according to the embodiment described above, by providing forecasted trajectory
creating means for creating a forecasted trajectory indicative of a forecasted position
of each elevator for a time axis for a predetermined period in the future, evaluation
value calculating means for calculating an evaluation value related to a positional
relationship between the forecasted trajectories of the respective elevators, and
allocating means for allocating a hall call to an elevator, more detailed information
can be analyzed for the arrangement of each car, and the information can be utilized
for allocation as well.
1. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising forecasted trajectory creating means (401) for creating a forecasted trajectory
indicative of a forecasted position of each elevator on a time axis for a predetermined
period in the future.
2. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising forecasted trajectory creating means (401) for creating a forecasted trajectory
indicative of a forecasted position of each elevator on a time axis for a predetermined
period in the future, and forecasted trajectory display means (H01) for displaying
the forecasted trajectory of each elevator.
3. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising forecasted trajectory creating means (401) for creating a forecasted trajectory
indicative of a forecasted position of each elevator on a time axis for a predetermined
period in the future, evaluation value calculating means (4) for calculating an evaluation
value related to a positional relationship between the forecasted trajectories of
the respective elevators.
4. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising forecasted trajectory creating means (401) for creating a forecasted trajectory
indicative of a forecasted position of each elevator on a time axis for a predetermined
period in the future, evaluation value calculating means (4) for calculating an evaluation
value related to a positional relationship between the forecasted trajectories of
the respective elevators, and hall call allocating means (7) for allocating an elevator
to a hall call based on the evaluation value.
5. An elevator group management system according to claim 3 or 4, characterized in that said positional relationship between the respective cages is an interval between
the respective cages.
6. An elevator group management system according to claim 3 or 4, characterized in that said positional relationship between the respective cages is a temporal interval
and/or a spatial interval between the respective cages.
7. An elevator group management system according to any of claims 1 to 6, characterized in that said predetermined period is set longer than a maximum forecasted arrival time in
all hall calls and cage calls.
8. An elevator group management system according to any of claims 1 to 7, characterized in that said predetermined period is set longer than one round time of each elevator.
9. An elevator group management system according to any of claims 1 to 8, characterized in that said forecasted trajectory creating means comprises means for forecasting a hall
call and cage call generation probability for a floor on which a hall call or a cage
call is not generated, and means for creating the forecasted trajectory near the floor
based on the generation probability.
10. An elevator group management system according to any of claims 1 to 9, characterized in that said forecasted trajectory creating means comprises means for forecasting a stop
probability for a hall call and a cage call which are not generated, and means for
creating the forecasted trajectory based on stops caused by a currently generated
hall call and cage call, and the forecasted stop probability.
11. An elevator group management system according to any of claims 1 to 10, characterized in that said forecasted trajectory creating means comprises means for adjusting a slope of
a forecasted trajectory upon movement of each floor in accordance with a traffic demand
of a building.
12. An elevator group management system according to any of claims 1 to 11, characterized in that said forecasted trajectory creating means creating a forecasted trajectory of each
elevator, and a trajectory which inverts the direction on the highest floor and the
lowest floor of serviced floors set for each elevator.
13. An elevator group management system according to any of claims 1 to 12, characterized in that said forecasted trajectory creating means creates a forecasted trajectory of an elevator
which does not have an allocated hall call or cage call so as to be parallel with
a time axis.
14. An elevator group management system according to any of claims 1 to 13, characterized in that said forecasted trajectory creating means creates a forecasted trajectory which includes
line segments having different slopes for each floor.
15. An elevator group management system according to any of claims 1 to 14, characterized in that said forecasted trajectory creating means creates a forecasted trajectory which includes
an inclined section due to running of each cage, and a horizontal section having a
length in accordance with a stop probability to each floor.
16. An elevator group management system according to any of claims 1 to 15, characterized in that said forecasted trajectory creating means creates a forecasted trajectory which includes
a line segment which connects from a floor on which each elevator is currently positioned
to one end floor in each of running directions of each elevator, and a line segment
which connects the one end floor to the other end floor.
17. An elevator group management system according to any of claims 1 to 16, characterized in that said forecasted trajectory creating means creates a forecasted trajectory which collectively
represents a plurality of non-stop floors by a single virtual floor, and makes a time
required to pass the virtual floor equal to a time required to pass the plurality
of non-stop floors.
18. An elevator group management system according to any of claims 2 and 7 to 17, characterized in that said forecasted trajectory display means (L001) comprises means for displaying the
position and/or direction of each elevator cage at a predetermined time within the
predetermined period.
19. An elevator group management system according to any of claims 2 and 7 to 18, characterized in that said forecasted trajectory display means (L001) comprises means for displaying the
forecasted trajectories before and after a certain elevator has been allocated to
a hall call.
20. An elevator group management system according to any of claims 2 and 7 to 19, characterized in that said forecasted trajectory display means (L001) comprises means for displaying the
forecasted trajectory of each elevator, and an operation trajectory of each elevator
before a current time point.
21. An elevator group management system according to any of claims 2 and 7 to 20, characterized by further comprising interval evaluating means (403) for evaluating an interval or
a positional relationship between the forecasted trajectories of the respective elevators,
wherein said forecasted trajectory display means comprises means (L001) for displaying
the forecasted trajectory, and means (L003) for displaying an interval evaluation
value by said interval evaluating means.
22. An elevator group management system according to any of claims 2 and 7 to 21, characterized in that said forecasted trajectory display means displays the forecasted trajectories of
the respective elevators in different colors.
23. A method of controlling an elevator group management system for managing a plurality
of elevators which service a plurality of floors, characterized by comprising a forecasted trajectory creating step for creating a forecasted trajectory
indicative of a forecasted position of each elevator on a time axis for a predetermined
period in the future, an evaluation value calculating step for calculating an evaluation
value related to a positional relationship between the forecasted trajectories of
the respective elevators, and a hall call allocating step for allocating an elevator
to a hall call based on the evaluation value.
24. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising means (3, 4) for calculating a plurality of evaluation values for a generated
hall call, general evaluation value calculating means (6) for calculating a general
evaluation value by weighting and adding the plurality of evaluation values, weight
calculating means (8) for calculating the value of a weight used by said general evaluation
value calculating means, and hall call allocating means (7) for allocating a hall
call to an elevator in accordance with the general evaluation value, wherein said
weight calculating means calculates the value of the weight based on a function which
continuously changes an output value in response to a change in an input.
25. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising means (3, 4) for calculating a plurality of evaluation values for a generated
hall call, general evaluation value calculating means (6) for calculating a general
evaluation value by weighting and adding the plurality of evaluation values, weight
calculating means (8) for calculating the value of a weight used by said general evaluation
value calculating means, and hall call allocating means (7) for allocating a hall
call to an elevator in accordance with the general evaluation value, wherein said
weight calculating means calculates the value of the weight based on a function which
is applied with an input that is a real number and continuously changes the value.
26. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising means (3, 4) for calculating a plurality of evaluation values for a generated
hall call, general evaluation value calculating means (6) for calculating a general
evaluation value by weighting and adding the plurality of evaluation values, weight
calculating means (8) for calculating the value of a weight used by said general evaluation
value calculating means, and hall call allocating means (7) for allocating a hall
call to an elevator in accordance with the general evaluation value, wherein said
weight calculating means calculates the value of the weight in accordance with a linear
function.
27. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising means (3, 4) for calculating a plurality of evaluation values for a generated
hall call, general evaluation value calculating means (6) for calculating a general
evaluation value by weighting and adding the plurality of evaluation values, weight
calculating means (8) for calculating the value of a weight used by said general evaluation
value calculating means, and hall call allocating means (7) for allocating a hall
call to an elevator in accordance with the general evaluation value, wherein said
weight calculating means calculates in accordance of a function of a plurality of
orders or a polynomial function.
28. An elevator group management system according to any of claims 24 to 27, characterized in that said function is applied with an input which is a variable and is a real number.
29. An elevator group management system according to any of claims 24 to 27, characterized in that the input of said function is a value related to the number of generated hall calls.
30. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising means (3, 4) for calculating a plurality of evaluation values for a generated
hall call, general evaluation value calculating means (6) for calculating a general
evaluation value by weighting and adding the plurality of evaluation values, weight
calculating means (8) for calculating the value of a weight used by said general evaluation
value calculating means, and hall call allocating means (7) for allocating a hall
call to an elevator in accordance with the general evaluation value, wherein said
weight calculating means comprises first setting means (12) for setting the value
of the weight based on a function which continuously changes an output value in response
to a change in an input, and second setting means (20, 21, 22) for setting the value
of the weight through a simulation of group management control using an actually measured
traffic demand.
31. An elevator group management system according to claim 7, characterized in that when a simulation of group management control for an actually measured traffic demand
has not been executed in the past, said first setting means sets the value of the
weight.
32. An elevator group management system according to claim 30, characterized by setting an initial value, an upper limit value, and a lower limit value by a function
which is applied with an input which is a real number and continuously changes the
value.
33. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising first evaluating means (3) for calculating an evaluation value for a waiting
time of a generated hall call, second evaluating means (4) for calculating an evaluation
value for an interval between the respective elevators, general evaluation value calculating
means (6) for calculating a general evaluation value by weighting and adding the plurality
of evaluation values, weight calculating means (8) for calculating the value of a
weight used by said general evaluation value calculating means, and hall call allocating
means (7) for allocating a hall call to an elevator in accordance with the general
evaluation value, wherein said weight calculating means calculates the value of the
weight based on a function which continuously changes an output value in response
to a change in an input.
34. An elevator group management system according to claim 33, characterized in that said weight calculating means calculates the value of the weight based on a function
of the number of calls generated for the group managed elevators, or the number of
users, or a function of an average waiting time.
35. A method of controlling an elevator group management system for managing a plurality
of elevators which service a plurality of floors, characterized by comprising an evaluation value calculating step for calculating a plurality of evaluation
values for a generated hall call, a general evaluation value calculating step for
calculating a general evaluation value by weighting and adding the plurality of evaluation
values, a weight calculating step for calculating the value of a weight used by said
general evaluation value calculating step, and a hall call allocating step for allocating
a hall call to an elevator in accordance with the general evaluation value, wherein
said weight calculating step calculates the value of the weight based on a function
which continuously changes an output value in response to a change in an input.
36. An elevator group management system for managing a plurality of elevators which service
a plurality of floors and comprising cage position forecasting means (402) for forecasting
the position of each elevator, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time, and allocating means (7) for allocating a hall call to an elevator in accordance
with the evaluation value, characterized by comprising evaluation time setting means (405) for setting the predetermined time
in accordance with a situation of generated hall calls and/or cage calls.
37. An elevator group management system for managing a plurality of elevators which service
a plurality of floors and comprising cage position forecasting means (402) for forecasting
the position of each elevator, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time, and allocating means (7) for allocating a hall call to an elevator in accordance
with the evaluation value, characterized by comprising evaluation time setting means (405) for setting the predetermined time
in accordance with the longest forecasted arrival time of all hall calls and cage
calls.
38. An elevator group management system according to claim 37, characterized in that said predetermined time is set to the longest forecasted arrival time or the vicinity
thereof.
39. An elevator group management system for managing a plurality of elevators which service
a plurality of floors and comprising cage position forecasting means (402) for forecasting
the position of each elevator, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time, and allocating means (7) for allocating a hall call to an elevator in accordance
with the evaluation value, characterized by comprising evaluation time setting means (405) for setting the predetermined time
in accordance with a forecasted arrival time of the temporally furthest hall call
or cage call.
40. An elevator group management system according to claim 37, characterized in that said predetermined time is set to the forecasted arrival time of the temporally furthest
hall call or cage call or the vicinity thereof.
41. An elevator group management system for managing a plurality of elevators which service
a plurality of floors and comprising cage position forecasting means (402) for forecasting
the position of each elevator, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time, and allocating means (7) for allocating a hall call to an elevator in accordance
with the evaluation value, characterized by comprising round time measuring means (408) for measuring one round time of each
elevator, and evaluation time setting means (405) for setting the predetermined time
in accordance with the measured round time.
42. An elevator group management system according to claim 41, characterized in that said round time is set to an average round time of each elevator.
43. An elevator group management system for managing a plurality of elevators which service
a plurality of floors and comprising cage position forecasting means (402) for forecasting
the position of each elevator, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time, and allocating means (7) for allocating a hall call to an elevator in accordance
with the evaluation value, characterized by comprising traffic flow measuring means (408) for measuring a traffic flow in a building,
and evaluation time setting means (405) for setting the predetermined time in accordance
with the measured traffic flow.
44. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising cage position forecasting means (402) for forecasting the position of
each elevator, evaluating means (4) for evaluating a positional relationship between
respective cages from a forecasted position of each cage after a predetermined time,
allocating means (7) for allocating a hall call to an elevator in accordance with
the evaluation value, and evaluation time setting means (405) for setting the predetermined
time for each allocation process by said allocating means.
45. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising cage position forecasting means (402) for forecasting the position of
each elevator, forecasted trajectory creating means (401) for creating a forecasted
trajectory of each elevator within a predetermined period based on the prediction
of the cage position, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time from the forecasted trajectory of each cage, allocating means (7) for allocating
a hall call to an elevator in accordance with the evaluation value, and evaluation
time setting means (405) for setting the predetermined time in accordance with a situation
of generated hall calls and/or cage calls.
46. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising cage position forecasting means (402) for forecasting the position of
each elevator, forecasted trajectory creating means (401) for creating a forecasted
trajectory of each elevator within a predetermined period based on the prediction
of the cage position, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time from the forecasted trajectory of each cage, and allocating means (7) for allocating
a hall call to an elevator in accordance with the evaluation value, and evaluation
time setting means (405) for setting the predetermined time in accordance with the
longest forecasted arrival time of all hall calls and cage calls.
47. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, wherein said elevator group management system comprises cage
position forecasting means (402) for forecasting the position of each elevator, forecasted
trajectory creating means (401) for creating a forecasted trajectory of each elevator
within a predetermined period based on the prediction of the cage position, evaluating
means (4) for evaluating a positional relationship between respective cages from a
forecasted position of each cage after a predetermined time from the forecasted trajectory
of each cage, and allocating means (7) for allocating a hall call to an elevator in
accordance with the evaluation value, characterized by comprising evaluation time setting means (405) for setting the predetermined time
in accordance with a forecasted arrival time of the temporally furthest hall call
or cage call.
48. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, wherein said elevator group management system comprises cage
position forecasting means (402) for forecasting the position of each elevator, forecasted
trajectory creating means (401) for creating a forecasted trajectory of each elevator
within a predetermined period based on the prediction of the cage position, evaluating
means (4) for evaluating a positional relationship between respective cages from a
forecasted position of each cage after a predetermined time from the forecasted trajectory
of each cage, and allocating means (7) for allocating a hall call to an elevator in
accordance with the evaluation value, characterized by comprising round time measuring means (408) for measuring one round time of each
elevator, and evaluation time setting means (405) for setting the predetermined time
in accordance with the measured round time.
49. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, wherein said elevator group management system comprises cage
position forecasting means (402) for forecasting the position of each elevator, forecasted
trajectory creating means (401) for creating a forecasted trajectory of each elevator
within a predetermined period based on the prediction of the cage position, evaluating
means (4) for evaluating a positional relationship between respective cages from a
forecasted position of each cage after a predetermined time from the forecasted trajectory
of each cage, and allocating means (7) for allocating a hall call to an elevator in
accordance with the evaluation value, characterized by comprising traffic flow measuring means (408) for measuring a traffic flow in a building,
and evaluation time setting means (405) for setting the predetermined time in accordance
with the measured traffic flow.
50. An elevator group management system for managing a plurality of elevators which service
a plurality of floors, characterized by comprising cage position forecasting means (402) for forecasting the position of
each elevator, forecasted trajectory creating means (401) for creating a forecasted
trajectory of each elevator within a predetermined period based on the prediction
of the cage position, evaluating means (4) for evaluating a positional relationship
between respective cages from a forecasted position of each cage after a predetermined
time from the forecasted trajectory of each cage, and allocating means (7) for allocating
a hall call to an elevator in accordance with the evaluation value, and evaluation
time setting means (405) for setting the predetermined time for each allocation process
by said allocating means.
51. An elevator group management system according to any of claims 36 to 50, characterized in that said positional relationship between the respective cages is an interval between
the respective cages.
52. An elevator group management system according to any of claims 36 to 50, characterized in that said positional relationship between the respective cages is a temporal interval
and/or a spatial interval between the respective cages.
53. A method of controlling an elevator group management system for managing a plurality
of elevators which service a plurality of floors, and comprising a cage position forecasting
step for forecasting the position of each elevator, a positional relationship evaluating
step for evaluating a positional relationship between respective cages from a forecasted
position of each cage after a predetermined time, and an allocating step for allocating
a hall call to an elevator in accordance with the evaluation value, characterized by comprising an evaluation time setting step for setting the predetermined time in
accordance with a situation of generated hall calls and/or cage calls.