Abstract:
Each car in a group of elevator cars in a building is determined to be available or not depending on whether it is assigned in the group, whether it is the only delayed car, whether it is fully loaded without intervening car calls which comprise all the car calls, whether it has intervening hall calls, and whether other cars in the group are fully loaded with or without some chance of offloading passengers before reaching a call to be assigned. Among available cars, assignment is made based on each car's membership in fuzzy sets relating to low, medium or high delay in that car responding to the call and each car's membership in fuzzy sets indicative of the extent to which assignment of that car will have no adverse effect or a very high adverse effect on the response to already-assigned hall calls. The call is assigned to the car with the highest summation of weighted memberships in the fuzzy sets.
Abstract:
A remaining response time for an elevator car under consideration for assignment to a newly registered hall call is estimated by using a neural network. The neural network or any other downstream module may be standardized for use in any building by use of an upstream fixed length stop description that summarizes the state of the building at the time of the registration of the new hall call for one or more postulated paths of each and every car under consideration for answering the new hall call.
Abstract:
To assign a car to a hall call such that cars A, B, C, D tend to be equally spaced apart and so that bunching of cars is avoided, the position of each car is predicted over a given period by estimating where it will arrive and leave each of its committed stops over that period for a given set of hall call/car call assignments, a bunching measure is calculated and a car to hall call assignment is made in response to the bunching measure.