A service estimation apparatus for an elevator adopting an estimated index with which service by the elevator can be estimated in any building and under any traffic state comprising a measurement apparatus to measure periods of service time and a microprocessor operating under program control to calculate a mean value and a variance of the periods of service time to set a reference value for designating a range of the periods of service time and to determine the estimated index, namely, an upper limit presumption value based on the mean value, the variance, and the reference value, and to determine an unachieved rate of service reference corresponding to the upper limit presumption value, the unachieved rate of service reference being a probability value at which the elevator periods of service time fall outside the range designated by the reference value.

A traffic volume estimating apparatus 1A estimates the traffic volumes of traffic apparatus, and a traffic flow presuming apparatus 1B presumes the traffic flows generating the estimated traffic volumes. A presumption function constructing apparatus 1C corrects the presumption functions of the traffic flow presuming apparatus 1B on actually measured traffic volumes, traffic flow presumption results and control results. A control result detecting apparatus 1G detects the control results and the drive results of the traffic apparatus. Further, a control parameter setting apparatus 1D sets control parameters on traffic flow presumption results, and corrects the control parameters according to the control results and the drive results.

An energy supply system operates to supply heat energies, such as cooling water, steam, heating water, etc. to a community, and the system has a function for predicting a future energy demand of the community and to correct it. In a system having an energy plant to store energy and an energy supply pipeline network for connecting the energy plant to the community, the system includes an energy demand plan making section for predicting an energy demand of the community on the basis of past cases of energy supply and for formulating an energy demand plan with respect to time, and an energy demand variation detecting section for determining a variation of the energy demand from the energy demand plan by using a personnel flow measured value measured by personnel flow measuring apparatuses provided at paths to or positions of the community as a parameter. The variation of the future energy demand of the community is predicted and energy which accomodates the determined variation can be prepared.

Elevator system with multiple cars (1-4) and a group controller (32) having signal processing means (CPU) controlling car dispatching from the lobby (L). During peak conditions (up-peak, down-peak and noontime), each car is dispatched and assigned to hall call floors having a large predicted number of passengers waiting on priority basis, resulting in queue length and waiting time at the lobby and upper floors being decreased, and system handling capacity increased. Estimations of future traffic flow levels for the floors for five minute intervals are made using traffic levels measured during the past few time intervals on that day as real time predictors, using a linear exponential smoothing model, and traffic levels measured during similar time intervals on previous similar days as historic traffic predictors, using a single exponential smoothing model. Combined prediction is used to assign hall calls to cars on priority basis for those floors having predicted high level of passenger traffic to limit maximum waiting time and car load. Noontime priority scheme is based on multiple queue sizes and percentages of maximum waiting time limits. Different waiting time limits can be used for lobby and above lobby up and down hall calls with automatic adjustment. During up-peak the lobby is given high priority. The lobby queue is predicted using passenger arrival rates and expected car arrival times. Down-peak operation uses multiple queue levels and percentages of waiting time limits, with estimated queues based on passenger arrival using car-to-hall-call travel time.

An elevator system containing a group of elevator cars (1-4) and a group controller (32) having signal processing means (CPU) for controlling the dispatching of the cars from a main floor or lobby (L) in relation to different group parameters. During up-peak conditions, each car is dispatched from the main floor to an individual plurality of contiguous floors, defining a "sector" (SN). Sectors are contiguous, and the number of sectors may be less than the number of cars, and a floor can be assigned to more than one sector. Floors that constitute a sector assigned exclusively to a car are displayed on an indicator (SI) at the lobby. Cars are selected for assignment by grouping floors into sectors and appropriately selecting sectors, so that each elevator car handles more or less an equal predicted traffic volume during varying traffic conditions, resulting in the queue length and waiting time at the lobby being decreased, and the handling capacity of the elevator system increased. Estimation of future traffic flow levels for the various floors for, for example, each five (5) minute interval, are made using traffic levels measured during the past few time intervals on the given day as real time predictors, using a linear exponential smoothing model, and traffic levels measured during similar time intervals on previous days as historic traffic predictors, using a single exonential smoothing model. The combined estimated traffic is then used to group floors into sectors ideally having at least nearly equal traffic volume for each time interval.