Abstract:
An elevator group supervision controlling apparatus has a response time predicting means, a passenger movement estimating means, a standby time predicting means, a candidate car selecting means, an allocating means, and an instructing means. The response time predicting means predicts response time to a car call from a remote call registering apparatus for respective cars. The passenger movement estimating means estimates passenger moving time based on a positional relationship between the remote call registering apparatus and a landing. The standby time predicting means predicts the standby times of each of the cars based on the response time and the passenger moving time. The candidate car selecting means includes cars for which standby time is shorter than a predetermined time interval in candidate cars, and excludes cars for which standby time is greater than or equal to the predetermined time interval from the candidate cars. The allocating means decides an allocated car from among the candidate cars if at least one of the cars has been included in the candidate cars. The instructing means generates an informing instruction to communicate to the remote call registering apparatus reinput requesting information that recommends an input operation at the landing call registering apparatus if all of the cars are excluded from the candidate cars.
Abstract:
The present disclosure provides a system and a method for controlling motion of a bank of elevators. The method includes accepting current requests for service by the bank of elevators, accepting a partial trajectory of a motion of a person moving in an environment serviced by the bank of elevators, and obtaining a probability of a future elevator request. The method further includes processing the partial trajectory with a neural network trained to estimate a weighted combination of probability density functions that indicates an arrival time distribution of the person, and generating a set of possible future requests jointly representing the probability of the future elevator request and the arrival time distribution. The method further includes optimizing a schedule of the bank of elevators to serve the current requests and the set of possible future requests, and controlling the bank of elevators according to the schedule.
Abstract:
Provided is an elevator group control system which is excellent in convenience and can prevent a decrease in operation efficiency even when an elevator is used by a group of a plurality of persons. For this purpose, there are installed in an elevator hall a destination operating panel by use of which users register their destination floors before boarding and a group boarding registering device for registering that users use an elevator as a group. The number of users expected when users use an elevator as a group is stored beforehand in a user head-count storage section. When registration of a destination floor by use of the destination operating panel has been performed at the same time with registration of a group use by use of the group boarding registering device, a car to be assigned to a hall car call is determined on the basis of the number of users stored in the user head-count storage section.
Abstract:
An elevator group supervisory control apparatus is obtained which can achieve efficient group supervisory control while preventing or reducing the possibility of collision and the safe stopping of an upper car and a lower car in one and the same shaft as much as possible. The apparatus includes a hall destination floor registration device 4 that is installed in each hall and has a destination floor registration function and a function of providing a predictive indication of a response car for each destination floor, a zone setting section 12 that sets priority zones and a common zone for each of upper and lower cars, an entry determination section 13 that determines whether the upper and lower cars can come into the common zone, a safe waiting section 14 that makes the cars 20 wait safely in accordance with the determination result of the entry determination section 13, a shunting section 15 that makes each car 20 move to a shunting floor as required at the instant when each car finished its service, a confinement time prediction section 16 that predicts a confinement time due to safe waiting when each car is assigned to a destination call generated in a hall, an evaluation value calculation section 17 that evaluates a waiting time, the confinement time, etc., upon assignment of each car, and an assignment section 18 that determines a final assigned car on the basis of the calculation result of the evaluation value calculation section 17.
Abstract:
An elevator group control apparatus to control an elevator system in which an upper car and a lower car serve in a single shaft and go up and down independently. If a new destination call is registered, a car travel range calculator provisionally assigns a car to the new destination call and calculates the travel range of the provisionally assigned car and the travel range of the other car in the same shaft. Based on the calculated travel ranges, an assignment candidate selector selects or rejects the car as a candidate for assignment to the new destination call. Later, several evaluation index values are calculated for each of the selected candidate cars. By comprehensively evaluating these calculated evaluation index values, a determination is made as to which car is to be assigned to the new destination call.
Abstract:
In an elevator having a group of double-deck cars, a hall call is assigned to one of the decks according to a priority scheme that takes into account the service capability of each car and its decks in a way that favors assignment of the call to the lagging deck of the car most capable of answering the call.
Abstract:
According to an aspect, there is provided a method and an apparatus (200) for determining an allocation decision for at least one elevator. In the solution existing calls are used in an elevator system as a first input in a machine learning module (202). The first input is processed with the machine learning module (202) to provide a first output comprising a first allocation decision. The first output is then used as a second input in an iterative module (204). The second input is processed with the iterative module (204) to provide a second output comprising a second allocation decision. The second allocation decision is provided to an elevator control module (212) and to an allocation decision storage (206) for further machine learning module training.