Elevator traffic predictions using historical data checked for certainty

Abstract

An elevator system (FIG. 1) employing a microprocessor-based group controller (FIG. 2) communicating with elevator cars (3,4, . . . ) to derive relative prediction values to be used in a scheme of ultimately assigning, e.g., cars to hall calls at a plurality of floors in the building, using appropriate dispatching strategies based on predicted traffic conditions. In the algorithm of the invention (FIG. 3) the building's inhabitants' behavior based on weekly events, daily events and real time events is predicted, with the events being used to derive relative prediction values based on the weighted summation of the real, daily and weekly values of the events. Weekly events are considered to be those that happened over a past number of weeks (e.g. 10 weeks) on the same day of the week; while daily events are those that happened over the past few days (e.g. 5 days). Real time events are those which are effectively currently happening, with the time frame of reference being sufficiently short to produce data which effectively can be considered 'real time' data, typically covering only a matter of some minutes (e.g. 4 minutes) or even less. In determining what events recorded in the daily and weekly historic data bases are to be used in deriving the predicted relative values, the degree of the certainty of the data is evaluated using two threshold considerations, and historic factors based on data which fails to have the requisite certainty is not used in the predictions.