Estimated Time of Arrival (ETA) Based Elevator Group Control Algorithm with More Accurate Estimation

We develop ETA (Estimated Time of Arrival) based elevator group control algorithms with more accurate estimations to minimize the average waiting time of the passengers. Following the principle of ETA estimations, the algorithms not only estimate the attending time of the new hall call, but also the delay that serving it will cause to successive unattended passengers that have been allocated to the same elevator. To increase the accuracy of this estimation we try to consider the number of extra stops caused by the new hall call and apply the three-passage concept to determine the service order of the hall calls: passage one (P1) hall calls are those that can be served by the elevator along its current travel direction, passage two (P2) hall calls require reversing the direction once, and passage three (P3) hall calls require two reversals. We propose two variants of the algorithm: a basic variant and a reallocation variant. The basic variant is based on the immediate allocation policy. The reallocation variant is based on coordination between the basic variant and a heuristic reallocation mechanism. The time complexity of both algorithms is O(MN), where M is the number of the elevators and N is the number of floors in the building. We have performed test runs with traffic data generated from realistic buildings ranging from 9 to 40 floors and with 3 to 8 shafts for typical traffic patterns. Our basic ETA algorithm reduces the average waiting time by 16 % and reduces the percentage of passengers who wait for more than 60 seconds by more than 3 % points when compared with the ETA algorithm of the commercially available Elevate simulator. Our reallocation variant further reduces the average waiting time by 7 % and the percentage of the passengers who wait for more than 60 seconds by more than 2 % points as compared with our basic algorithm.