Janne Sorsa

Optimal control of double-deck elevator group using genetic algorithm

We shall introduce the principles of optimal routing of double-deck elevators. The elevator routing problem is formulated as an integer programming problem and it is solved using a genetic algorithm in a real-time system. The optimal routes of double-deck elevators have not been considered earlier in the literature. The simulation results are analyzed with discussion about the significance of the method.

A study on the arrival process of lift passengers in a multi-storey office building

This article presents a study on the process of how passengers arrive at lift lobbies to travel to their destinations. Earlier studies suggest that passengers arrive at the lift lobbies individually with exponentially distributed inter-arrival times, that is, according to a Poisson process. This study was carried out in a multi-storey office building. The data was collected using a questionnaire, digital video recordings and the lift monitoring system. The results show that, in the studied building, passengers arrive in batches whose size varies with the time of day and the floor utilization. In addition, the batch arrivals follow a time-inhomogeneous Poisson process with piecewise constant arrival rates. Practical applications : This article contributes to the basic understanding of passenger behaviour, and how people move around in buildings and arrive at the lift lobbies. It is proposed that the model for the passenger arrival process should take into account that passengers do not always arrive individually but also in batches. The passenger arrival process affects the design of elevators. It will also affect the passenger generation in building traffic simulations.

The Elevator Trip Origin-Destination Matrix Estimation Problem

In this paper, we consider the problem of finding the passenger counts for the origin-destination pairs of a particular single transit route called elevator trip. Assuming that passengers first alight and then board a stopping elevator, we can define an elevator trip as successive stops in one direction of travel with passengers inside the elevator. The elevator trip origin-destination passenger counts, i.e., elevator trip origin-destination matrices, estimated for a given time interval can be combined into a building origin-destination matrix that describes the passenger flow between every pair of floors in the building during that interval. The building origin-destination matrices of successive intervals form traffic statistics that can be used to forecast passenger traffic. The forecasts model the uncertainties related to future passengers, and need to be taken into account in elevator dispatching to make robust dispatching decisions in constantly changing traffic conditions. Many methods exist for estimating an origin-destination matrix for a single transit route such as a bus line. These methods estimate average origin-destination passenger counts from observations made during a given time period on the same route. Because an elevator trip is request driven, there may not be two similar elevator trips even within a day. This means that we need to estimate a separate origin-destination matrix for each elevator trip. A natural requirement then is that the estimated origin-destination passenger counts are integer valued. We formulate the elevator trip origin-destination matrix estimation problem as a box-constrained integer least squares problem, and present branch-and-bound-based algorithms for finding all solutions to the problem. The performance of the algorithms with respect to execution time is studied based on numerical experiments. The results show that the formulation and the algorithms are fast enough for solving elevator trip origin-destination matrix estimation problems in a real elevator group control application.

Assignment formulation for the Elevator Dispatching Problem with destination control and its performance analysis

This paper studies the Elevator Dispatching Problem arising in destination controls. In many of the presented methods to the problem a routing aspect is not considered; decision variables specify only request-to-elevator assignments and the service order of the requests is determined by applying a heuristic rule called the collective control principle. However, quality of this approach is rarely investigated. In this paper the approach is compared with a formulation defining explicitly the elevator routes. The average waiting time as well as average journey time are used as objective functions in the comparisons. Computational experiments with the former objective function on random instances arising during light and normal traffic conditions indicate that both approaches very often produce the same solution while with the latter one the situation is the opposite. Some well-known traffic patterns are also analyzed to identify cases in which the optimal solutions of these approaches are equal.

Evacuation Simulation and Human Behaviour Models in Tall Buildings

In tall buildings, staircases are usually the only means for evacuation. It can take more than two hours for an occupant to reach a refuge floor by the stairs owing to congestion and long travel distance. In a non-fire situation, elevators also could be used in evacuation. Where there are several alternative transport devices available for egress, occupants need to decide which one to use. This decision is based on the occupant’s knowledge of the egress routes in the building. Evacuation models consider human behaviour mostly for horizontal movement and low buildings, without considering elevators as a means of egress. In this article, we describe vertical transportation and agent-based human behaviour models of the Building Traffic Simulator. The evacuation of the World Trade Centre is simulated and the results are compared with published data.